---
title: "A Survey on LLM-based Conversational User Simulation (2026)"
description: "This survey organizes the fast-growing literature on using large language models to imitate users in dialogue. 218 references."
authors: ["Bo Ni", "Yu Wang", "Leyao Wang", "Branislav Kveton", "Franck Dernoncourt", "Yu Xia", "Hongjie Chen", "Reuben Luera", "Samyadeep Basu", "Subhojyoti Mukherjee", "Puneet Mathur", "Nesreen K. Ahmed", "Junda Wu", "Li Li", "Huixin Zhang", "Ruiyi Zhang", "Tong Yu", "Sungchul Kim", "Jiuxiang Gu", "Zhengzhong Tu", "Alexa Siu", "Zichao Wang", "Seunghyun Yoon", "Nedim Lipka", "Namyong Park", "Zihao Lin", "Trung Bui", "Yue Zhao", "Tyler Derr", "Ryan A. Rossi"]
year: 2026
venue: "Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)"
source: "https://aclanthology.org/2026.eacl-long.200/"
doi: "10.18653/v1/2026.eacl-long.200"
licence: "CC BY 4.0 (ACL Anthology)"
licence_url: "https://creativecommons.org/licenses/by/4.0/"
summary_licence: "Elamur Cosmic License"
canonical: "https://research.elamur.ai/free/en/papers/ni-2026-survey-llm-based-conversational-user/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/ni-2026-survey-llm-based-conversational-user/)

[home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [2026](https://md.research.elamur.ai/free/en/papers/2026/page/9/) / A Survey on LLM-based Conversational User Simulation

# A Survey on LLM-based Conversational User Simulation

**Authors:** [Bo Ni](https://md.research.elamur.ai/free/en/authors/bo-ni/), [Yu Wang](https://md.research.elamur.ai/free/en/authors/yu-wang/), Leyao Wang, [Branislav Kveton](https://md.research.elamur.ai/free/en/authors/branislav-kveton/), [Franck Dernoncourt](https://md.research.elamur.ai/free/en/authors/franck-dernoncourt/), [Yu Xia](https://md.research.elamur.ai/free/en/authors/yu-xia/), [Hongjie Chen](https://md.research.elamur.ai/free/en/authors/hongjie-chen/), Reuben Luera, [Samyadeep Basu](https://md.research.elamur.ai/free/en/authors/samyadeep-basu/), [Subhojyoti Mukherjee](https://md.research.elamur.ai/free/en/authors/subhojyoti-mukherjee/), [Puneet Mathur](https://md.research.elamur.ai/free/en/authors/puneet-mathur/), [Nesreen K. Ahmed](https://md.research.elamur.ai/free/en/authors/nesreen-k-ahmed/), [Junda Wu](https://md.research.elamur.ai/free/en/authors/junda-wu/), [Li Li](https://md.research.elamur.ai/free/en/authors/li-li/), Huixin Zhang, [Ruiyi Zhang](https://md.research.elamur.ai/free/en/authors/ruiyi-zhang/), [Tong Yu](https://md.research.elamur.ai/free/en/authors/tong-yu/), [Sungchul Kim](https://md.research.elamur.ai/free/en/authors/sungchul-kim/), Jiuxiang Gu, Zhengzhong Tu, Alexa Siu, [Zichao Wang](https://md.research.elamur.ai/free/en/authors/zichao-wang/), Seunghyun Yoon, [Nedim Lipka](https://md.research.elamur.ai/free/en/authors/nedim-lipka/), Namyong Park, Zihao Lin, [Trung Bui](https://md.research.elamur.ai/free/en/authors/trung-bui/), [Yue Zhao](https://md.research.elamur.ai/free/en/authors/yue-zhao/), Tyler Derr and [Ryan A. Rossi](https://md.research.elamur.ai/free/en/authors/ryan-a-rossi/) · **Year:** 2026 · **Venue:** [Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)](https://md.research.elamur.ai/free/en/venues/eacl/) ([EACL 2026](https://md.research.elamur.ai/free/en/venues/eacl/2026/)) · **Publisher:** [Association for Computational Linguistics](https://md.research.elamur.ai/free/en/publishers/association-for-computational-linguistics/) · **Licence:** [CC BY 4.0 (ACL Anthology)](https://creativecommons.org/licenses/by/4.0/)

**Links:** [Publisher's page](https://aclanthology.org/2026.eacl-long.200/) · [PDF](https://aclanthology.org/2026.eacl-long.200.pdf) · [DOI 10.18653/v1/2026.eacl-long.200](https://doi.org/10.18653/v1/2026.eacl-long.200) · [OpenAlex](https://openalex.org/W7140137267)

**Citations:** 1 citations (OpenAlex, 2026-10-14)

## Summary
This survey organizes the fast-growing literature on using large language models to imitate users in dialogue. Earlier statistical user models, such as Bradley-Terry-Luce, Plackett-Luce, collaborative filtering and click models, needed substantial user data and were usually built for one task. LLMs can instead produce rich, context-aware synthetic conversations through prompting alone. The authors note that no prior survey treats conversational user simulation as its own sub-field. They frame the task formally: predict a participant's next utterance from the dialogue history and that participant's context.

Existing work is arranged around three questions:
- **Who** is simulated, from a generic user down to a specific individual.
- **What** is simulated.
- **How** the conversation is produced, including core techniques and evaluation methods.

The paper also catalogs datasets and applications. It closes with open problems: persona drift in long dialogues, limited behavioral diversity, and bias or toxicity. The survey gives researchers building synthetic users for evaluation, training or data augmentation a shared vocabulary and map of the field. However, it runs no benchmark of its own.

## Key points
- The "Who" axis has five levels of user granularity: general (default persona), persona-level (an explicit set of demographic, interest or style attributes), role play (a real or fictional identity like "Mark Zuckerberg at 20"), individual (full personal history such as chat logs), and hybrid.
- The core formulation models P(u_t | C_{t-1}, Ψ_p). This covers user-user, user-system and multi-party conversations.
- Applications include:
  - data augmentation for sparse user histories;
  - conversational recommendation;
  - educational companions;
  - HCI interface testing;
  - video question answering with Elo-style arena evaluation.
- The main open challenges are:
  - consistency over long conversations;
  - simulated users who are too cooperative or too homogeneous;
  - neglect of multi-user settings;
  - bias and toxic output;
  - ethical risks of role-playing public figures.
- The paper appeared in EACL 2026 (Volume 1: Long Papers, pp. 4266–4301). It is a collaboration led by Vanderbilt University and Adobe Research.

*Our summary of the paper, in our own words — not its text. The work belongs to its authors; read it at the links above.*

📚 Shelves (4): [🖥️ Computer Science](https://md.research.elamur.ai/free/en/shelves/computer-science/) · 16,667 works · [🤖 Artificial Intelligence](https://md.research.elamur.ai/free/en/shelves/computer-science/artificial-intelligence/) · 16,194 works · [🎭 Arts and Humanities](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/) · 16,039 works · [🗣️ Language and Linguistics](https://md.research.elamur.ai/free/en/shelves/arts-and-humanities/language-and-linguistics/) · 15,891 works

🧭 Topics (1): [🗨️ Dialogue systems](https://md.research.elamur.ai/free/en/topics/dialogue-systems/) · 624 works

## Cite

Cite as: Bo Ni, Yu Wang, Leyao Wang, Branislav Kveton, Franck Dernoncourt, Yu Xia, Hongjie Chen, Reuben Luera, Samyadeep Basu, Subhojyoti Mukherjee, Puneet Mathur, Nesreen K. Ahmed, Junda Wu, Li Li, Huixin Zhang, Ruiyi Zhang, Tong Yu, Sungchul Kim, Jiuxiang Gu, Zhengzhong Tu, Alexa Siu, Zichao Wang, Seunghyun Yoon, Nedim Lipka, Namyong Park, Zihao Lin, Trung Bui, Yue Zhao, Tyler Derr and Ryan A. Rossi. 2026. A Survey on LLM-based Conversational User Simulation. Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers).

The paper itself, not this page. BibTeX from the library's record of the work.

```bibtex
@inproceedings{ni2026survey,
  title = {{A Survey on LLM-based Conversational User Simulation}},
  author = {Bo Ni, Yu Wang, Leyao Wang, Branislav Kveton, Franck Dernoncourt, Yu Xia, Hongjie Chen, Reuben Luera, Samyadeep Basu, Subhojyoti Mukherjee, Puneet Mathur, Nesreen K. Ahmed, Junda Wu, Li Li, Huixin Zhang, Ruiyi Zhang, Tong Yu, Sungchul Kim, Jiuxiang Gu, Zhengzhong Tu, Alexa Siu, Zichao Wang, Seunghyun Yoon, Nedim Lipka, Namyong Park, Zihao Lin, Trung Bui, Yue Zhao, Tyler Derr and Ryan A. Rossi},
  booktitle = {Proceedings of the 19th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)},
  year = {2026},
  doi = {10.18653/v1/2026.eacl-long.200},
  url = {https://doi.org/10.18653/v1/2026.eacl-long.200}
}
```

- [← previous A Survey of Deep Learning for Geometry Problem Solving](https://md.research.elamur.ai/free/en/papers/ma-2026-survey-deep-learning-geometry-problem/)
- [next → Aatman at SemEval-2026 Task 9: Transfer Learning for Multilingual Polarization Detection](https://md.research.elamur.ai/free/en/papers/vaidya-2026-aatman-semeval-2026-task-9/)
- [↑ back to papers of 2026](https://md.research.elamur.ai/free/en/papers/2026/page/9/)

## References

218 references, 52 of them with a card of ours. ↗ leads to the work, «find» searches for one we have no id for yet.

1. Zahra Abbasiantaeb, Yifei Yuan, Evangelos Kanoulas, and Mohammad Aliannejadi. 2024. Let the llms talk: Simulating human-to-human conversational QA via zero-shot llm-to-llm interactions. In Proceedings of the 17th ACM International Conference on Web Search and Data Mining, WSDM 2024, pages 8–17. ACM. [find](https://scholar.google.com/scholar?q=Zahra+Abbasiantaeb%2C+Yifei+Yuan%2C+Evangelos+Kanoulas%2C+and+Mohammad+Aliannejadi%2E+2024%2E+Let+the+llms+talk%3A+Simulating+human%2Dto%2Dhuman+conversational+QA+via+zero%2Dshot+llm%2Dto%2Dllm+interactions%2E+In+Proceedings)
2. Jafar Afzali, Aleksander Mark Drzewiecki, Krisztian Balog, and Shuo Zhang. 2023. Usersimcrs: A user simulation toolkit for evaluating conversational recommender systems. In Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, WSDM 2023, pages 1160–1163. ACM. [find](https://scholar.google.com/scholar?q=Jafar+Afzali%2C+Aleksander+Mark+Drzewiecki%2C+Krisztian+Balog%2C+and+Shuo+Zhang%2E+2023%2E+Usersimcrs%3A+A+user+simulation+toolkit+for+evaluating+conversational+recommender+systems%2E+In+Proceedings+of+the+Sixteent)
3. Jaewoo Ahn, Yeda Song, Sangdoo Yun, and Gunhee Kim. 2023. MPCHAT: towards multimodal persona-grounded conversation. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2023, pages 3354–3377. Association for Computational Linguistics… [find](https://scholar.google.com/scholar?q=Jaewoo+Ahn%2C+Yeda+Song%2C+Sangdoo+Yun%2C+and+Gunhee+Kim%2E+2023%2E+MPCHAT%3A+towards+multimodal+persona%2Dgrounded+conversation%2E+In+Proceedings+of+the+61st+Annual+Meeting+of+the+Association+for+Computational+Lingu)
4. Krisztian Balog and ChengXiang Zhai. 2023. User simulation for evaluating information access systems. In Proceedings of the Annual International ACM SIGIR Conference on Research and Development in Information Retrieval in the Asia Pacific Region, pages 302–305. [find](https://scholar.google.com/scholar?q=Krisztian+Balog+and+ChengXiang+Zhai%2E+2023%2E+User+simulation+for+evaluating+information+access+systems%2E+In+Proceedings+of+the+Annual+International+ACM+SIGIR+Conference+on+Research+and+Development+in+Inf)
5. Krisztian Balog and ChengXiang Zhai. 2025. User simulation in the era of generative AI: user modeling, synthetic data generation, and system evaluation. CoRR, abs/2501.04410. — [arXiv:2501.04410](https://arxiv.org/abs/2501.04410) [find](https://scholar.google.com/scholar?q=Krisztian+Balog+and+ChengXiang+Zhai%2E+2025%2E+User+simulation+in+the+era+of+generative+AI%3A+user+modeling%2C+synthetic+data+generation%2C+and+system+evaluation%2E+CoRR%2C+abs%2F2501%2E04410%2E+%E2%80%94+%5BarXiv%3A2501%2E04410%5D%28http)
6. Kathy Baxter, Catherine Courage, and Kelly Caine. 2015. Understanding your users: a practical guide to user research methods. Morgan Kaufmann. [find](https://scholar.google.com/scholar?q=Kathy+Baxter%2C+Catherine+Courage%2C+and+Kelly+Caine%2E+2015%2E+Understanding+your+users%3A+a+practical+guide+to+user+research+methods%2E+Morgan+Kaufmann%2E)
7. Nolwenn Bernard and Krisztian Balog. 2024. Identifying breakdowns in conversational recommender systems using user simulation. In ACM Conversational User Interfaces 2024, CUI 2024, page 26. ACM. [find](https://scholar.google.com/scholar?q=Nolwenn+Bernard+and+Krisztian+Balog%2E+2024%2E+Identifying+breakdowns+in+conversational+recommender+systems+using+user+simulation%2E+In+ACM+Conversational+User+Interfaces+2024%2C+CUI+2024%2C+page+26%2E+ACM%2E)
8. Léon Bottou, Jonas Peters, Joaquin Quiñonero Candela, Denis Xavier Charles, Max Chickering, Elon Portugaly, Dipankar Ray, Patrice Y. Simard, and Ed Snelson. 2013. Counterfactual reasoning and learning systems: The example of computational advertising. Journal of Machine Learning Research, 14(1):3207… [find](https://scholar.google.com/scholar?q=L%C3%A9on+Bottou%2C+Jonas+Peters%2C+Joaquin+Qui%C3%B1onero+Candela%2C+Denis+Xavier+Charles%2C+Max+Chickering%2C+Elon+Portugaly%2C+Dipankar+Ray%2C+Patrice+Y%2E+Simard%2C+and+Ed+Snelson%2E+2013%2E+Counterfactual+reasoning+and+learning)
9. Ralph Allan Bradley and Milton E. Terry. 1952. Rank analysis of incomplete block designs: I. the method of paired comparisons. Biometrika, 39(3-4):324– 345. [find](https://scholar.google.com/scholar?q=Ralph+Allan+Bradley+and+Milton+E%2E+Terry%2E+1952%2E+Rank+analysis+of+incomplete+block+designs%3A+I%2E+the+method+of+paired+comparisons%2E+Biometrika%2C+39%283%2D4%29%3A324%E2%80%93+345%2E)
10. Timo Breuer, Norbert Fuhr, and Philipp Schaer. 2024. Validating synthetic usage data in living lab environments. ACM Journal of Data and Information Quality, 16(1):5:1–5:33. [find](https://scholar.google.com/scholar?q=Timo+Breuer%2C+Norbert+Fuhr%2C+and+Philipp+Schaer%2E+2024%2E+Validating+synthetic+usage+data+in+living+lab+environments%2E+ACM+Journal+of+Data+and+Information+Quality%2C+16%281%29%3A5%3A1%E2%80%935%3A33%2E)
11. Pawel Budzianowski, Tsung-Hsien Wen, Bo-Hsiang Tseng, Iñigo Casanueva, Stefan Ultes, Osman Ramadan, and Milica Gasic. 2018. [Multiwoz - A large-scale multi-domain wizard-of-oz dataset for task-oriented dialogue modelling](https://md.research.elamur.ai/free/en/papers/budzianowski-2018-multiwoz-large-scale-multi-domain/). In Proceedings of the 2018 Conference on Empirical Methods in Natural Language…
12. Bill Byrne, Karthik Krishnamoorthi, Chinnadhurai Sankar, Arvind Neelakantan, Ben Goodrich, Daniel Duckworth, Semih Yavuz, Amit Dubey, Kyu-Young Kim, and Andy Cedilnik. 2019. [Taskmaster-1: Toward a realistic and diverse dialog dataset](https://md.research.elamur.ai/free/en/papers/byrne-2019-taskmaster-1-realistic-diverse-dialog/). In Proceedings of the 2019 Conference on Empirical Methods in Nat…
13. Yuanpu Cao, Tianrong Zhang, Bochuan Cao, Ziyi Yin, Lu Lin, Fenglong Ma, and Jinghui Chen. 2024. Personalized steering of large language models: Versatile steering vectors through bi-directional preference optimization. In Advances in Neural Information Processing Systems 38: Annual Conference on Neu… [find](https://scholar.google.com/scholar?q=Yuanpu+Cao%2C+Tianrong+Zhang%2C+Bochuan+Cao%2C+Ziyi+Yin%2C+Lu+Lin%2C+Fenglong+Ma%2C+and+Jinghui+Chen%2E+2024%2E+Personalized+steering+of+large+language+models%3A+Versatile+steering+vectors+through+bi%2Ddirectional+prefer)
14. Grace Chan and Andrew T. A. Wood. 1999. Simulation of stationary gaussian vector fields. Statistics and Computing, 9(4):265–268. [find](https://scholar.google.com/scholar?q=Grace+Chan+and+Andrew+T%2E+A%2E+Wood%2E+1999%2E+Simulation+of+stationary+gaussian+vector+fields%2E+Statistics+and+Computing%2C+9%284%29%3A265%E2%80%93268%2E)
15. Yung-Chieh Chan, George Pu, Apaar Shanker, Parth Suresh, Penn Jenks, John Heyer, and Sam Denton. 2024. Balancing cost and effectiveness of synthetic data generation strategies for llms. CoRR, abs/2409.19759. — [arXiv:2409.19759](https://arxiv.org/abs/2409.19759) [find](https://scholar.google.com/scholar?q=Yung%2DChieh+Chan%2C+George+Pu%2C+Apaar+Shanker%2C+Parth+Suresh%2C+Penn+Jenks%2C+John+Heyer%2C+and+Sam+Denton%2E+2024%2E+Balancing+cost+and+effectiveness+of+synthetic+data+generation+strategies+for+llms%2E+CoRR%2C+abs%2F2409)
16. Olivier Chapelle and Ya Zhang. 2009. A dynamic bayesian network click model for web search ranking. In Proceedings of the 18th International Conference on World Wide Web, WWW 2009, pages 1–10. ACM. [find](https://scholar.google.com/scholar?q=Olivier+Chapelle+and+Ya+Zhang%2E+2009%2E+A+dynamic+bayesian+network+click+model+for+web+search+ranking%2E+In+Proceedings+of+the+18th+International+Conference+on+World+Wide+Web%2C+WWW+2009%2C+pages+1%E2%80%9310%2E+ACM%2E)
17. Derek Chen, Howard Chen, Yi Yang, Alexander Lin, and Zhou Yu. 2021. Action-based conversations dataset: A corpus for building more in-depth task-oriented dialogue systems. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Lang… [find](https://scholar.google.com/scholar?q=Derek+Chen%2C+Howard+Chen%2C+Yi+Yang%2C+Alexander+Lin%2C+and+Zhou+Yu%2E+2021%2E+Action%2Dbased+conversations+dataset%3A+A+corpus+for+building+more+in%2Ddepth+task%2Doriented+dialogue+systems%2E+In+Proceedings+of+the+2021+C)
18. Hongzhan Chen, Hehong Chen, Ming Yan, Wenshen Xu, Gao Xing, Weizhou Shen, Xiaojun Quan, Chenliang Li, Ji Zhang, and Fei Huang. 2024a. Socialbench: Sociality evaluation of role-playing conversational agents. In Findings of the Association for Computational Linguistics, ACL 2024, pages 2108– 2126. Ass… [find](https://scholar.google.com/scholar?q=Hongzhan+Chen%2C+Hehong+Chen%2C+Ming+Yan%2C+Wenshen+Xu%2C+Gao+Xing%2C+Weizhou+Shen%2C+Xiaojun+Quan%2C+Chenliang+Li%2C+Ji+Zhang%2C+and+Fei+Huang%2E+2024a%2E+Socialbench%3A+Sociality+evaluation+of+role%2Dplaying+conversational+a)
19. Jiangjie Chen, Xintao Wang, Rui Xu, Siyu Yuan, Yikai Zhang, Wei Shi, Jian Xie, Shuang Li, Ruihan Yang, Tinghui Zhu, Aili Chen, Nianqi Li, Lida Chen, Caiyu Hu, Siye Wu, Scott Ren, Ziquan Fu, and Yanghua Xiao. 2024b. [From persona to personalization: A survey on role-playing language agents](https://md.research.elamur.ai/free/en/papers/chen-2024-persona-personalization-survey-role-playing/). Transactio…
20. Kevin Chen, Marco F. Cusumano-Towner, Brody Huval, Aleksei Petrenko, Jackson Hamburger, Vladlen Koltun, and Philipp Krähenbühl. 2025a. Reinforcement learning for long-horizon interactive LLM agents. CoRR, abs/2502.01600. — [arXiv:2502.01600](https://arxiv.org/abs/2502.01600) [find](https://scholar.google.com/scholar?q=Kevin+Chen%2C+Marco+F%2E+Cusumano%2DTowner%2C+Brody+Huval%2C+Aleksei+Petrenko%2C+Jackson+Hamburger%2C+Vladlen+Koltun%2C+and+Philipp+Kr%C3%A4henb%C3%BChl%2E+2025a%2E+Reinforcement+learning+for+long%2Dhorizon+interactive+LLM+agents%2E+C)
21. Maximillian Chen, Ruoxi Sun, Tomas Pfister, and Sercan Ö. Arik. 2025b. Learning to clarify: Multi-turn conversations with action-based contrastive self-training. In The Thirteenth International Conference on Learning Representations, ICLR 2025. [find](https://scholar.google.com/scholar?q=Maximillian+Chen%2C+Ruoxi+Sun%2C+Tomas+Pfister%2C+and+Sercan+%C3%96%2E+Arik%2E+2025b%2E+Learning+to+clarify%3A+Multi%2Dturn+conversations+with+action%2Dbased+contrastive+self%2Dtraining%2E+In+The+Thirteenth+International+Confer)
22. Qian Chen, Zhu Zhuo, and Wen Wang. 2019. BERT for joint intent classification and slot filling. CoRR, abs/1902.10909. [find](https://scholar.google.com/scholar?q=Qian+Chen%2C+Zhu+Zhuo%2C+and+Wen+Wang%2E+2019%2E+BERT+for+joint+intent+classification+and+slot+filling%2E+CoRR%2C+abs%2F1902%2E10909%2E)
23. Stanley F. Chen, Doug Beeferman, and Ronald Rosenfeld. 1998. Evaluation metrics for language models. In DARPA Broadcast News Transcription and Understanding Workshop. [find](https://scholar.google.com/scholar?q=Stanley+F%2E+Chen%2C+Doug+Beeferman%2C+and+Ronald+Rosenfeld%2E+1998%2E+Evaluation+metrics+for+language+models%2E+In+DARPA+Broadcast+News+Transcription+and+Understanding+Workshop%2E)
24. Yirong Chen, Xiaofen Xing, Jingkai Lin, Huimin Zheng, Zhenyu Wang, Qi Liu, and Xiangmin Xu. 2023. Soulchat: Improving llms’ empathy, listening, and comfort abilities through fine-tuning with multi-turn empathy conversations. In Findings of the Association for Computational Linguistics: EMNLP 2023, p… [find](https://scholar.google.com/scholar?q=Yirong+Chen%2C+Xiaofen+Xing%2C+Jingkai+Lin%2C+Huimin+Zheng%2C+Zhenyu+Wang%2C+Qi+Liu%2C+and+Xiangmin+Xu%2E+2023%2E+Soulchat%3A+Improving+llms%E2%80%99+empathy%2C+listening%2C+and+comfort+abilities+through+fine%2Dtuning+with+multi%2Dtur)
25. Prateek Chhikara, Dev Khant, Saket Aryan, Taranjeet Singh, and Deshraj Yadav. 2025. [Mem0: Building production-ready AI agents with scalable long-term memory](https://md.research.elamur.ai/free/en/papers/chhikara-2025-mem0-building-production-ready-ai/). CoRR, abs/2504.19413.
26. Won Ik Cho, Yoon Kyung Lee, Seoyeon Bae, Jihwan Kim, Sangah Park, Moosung Kim, Sowon Hahn, and Nam Soo Kim. 2023. When crowd meets persona: Creating a large-scale open-domain persona dialogue corpus. CoRR, abs/2304.00350. — [arXiv:2304.00350](https://arxiv.org/abs/2304.00350) [find](https://scholar.google.com/scholar?q=Won+Ik+Cho%2C+Yoon+Kyung+Lee%2C+Seoyeon+Bae%2C+Jihwan+Kim%2C+Sangah+Park%2C+Moosung+Kim%2C+Sowon+Hahn%2C+and+Nam+Soo+Kim%2E+2023%2E+When+crowd+meets+persona%3A+Creating+a+large%2Dscale+open%2Ddomain+persona+dialogue+corpus%2E+)
27. Paul F. Christiano, Jan Leike, Tom B. Brown, Miljan Martic, Shane Legg, and Dario Amodei. 2017. Deep reinforcement learning from human preferences. In Advances in Neural Information Processing Systems 30: Annual Conference on Neural Information Processing Systems 2017, NeurIPS 2017, pages 4299– 4307… [find](https://scholar.google.com/scholar?q=Paul+F%2E+Christiano%2C+Jan+Leike%2C+Tom+B%2E+Brown%2C+Miljan+Martic%2C+Shane+Legg%2C+and+Dario+Amodei%2E+2017%2E+Deep+reinforcement+learning+from+human+preferences%2E+In+Advances+in+Neural+Information+Processing+Systems)
28. Ameet Deshpande, Vishvak Murahari, Tanmay Rajpurohit, Ashwin Kalyan, and Karthik Narasimhan. 2023. [Toxicity in chatgpt: Analyzing persona-assigned language models](https://md.research.elamur.ai/free/en/papers/deshpande-2023-toxicity-chatgpt-analyzing-persona-assigned/). In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 1236–1270. Association for Computational Linguistics.
29. Kaustubh Dhole. 2024. Kaucus-knowledgeable user simulators for training large language models. In Proceedings of the 1st Workshop on Simulating Conversational Intelligence in Chat, SCI-CHAT 2024, pages 53–65. [find](https://scholar.google.com/scholar?q=Kaustubh+Dhole%2E+2024%2E+Kaucus%2Dknowledgeable+user+simulators+for+training+large+language+models%2E+In+Proceedings+of+the+1st+Workshop+on+Simulating+Conversational+Intelligence+in+Chat%2C+SCI%2DCHAT+2024%2C+page)
30. Emily Dinan, Stephen Roller, Kurt Shuster, Angela Fan, Michael Auli, and Jason Weston. 2019. [Wizard of wikipedia: Knowledge-powered conversational agents](https://md.research.elamur.ai/free/en/papers/dinan-2018-wizard-wikipedia-knowledge-powered-conversational/). In The Seventh International Conference on Learning Representations, ICLR 2019.
31. Ning Ding, Yulin Chen, Bokai Xu, Yujia Qin, Shengding Hu, Zhiyuan Liu, Maosong Sun, and Bowen Zhou. 2023. [Enhancing chat language models by scaling high-quality instructional conversations](https://md.research.elamur.ai/free/en/papers/ding-2023-enhancing-chat-language-models-scaling/). In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, pages 3…
32. Yilun Du, Shuang Li, Antonio Torralba, Joshua B. Tenenbaum, and Igor Mordatch. 2024. [Improving factuality and reasoning in language models through multiagent debate](https://md.research.elamur.ai/free/en/papers/du-2023-improving-factuality-reasoning-language-models/). In Forty-first International Conference on Machine Learning, ICML 2024.
33. Miroslav Dudík, Dumitru Erhan, John Langford, and Lihong Li. 2014. Doubly robust policy evaluation and optimization. Statistical Science, 29(4):485–511. [find](https://scholar.google.com/scholar?q=Miroslav+Dud%C3%ADk%2C+Dumitru+Erhan%2C+John+Langford%2C+and+Lihong+Li%2E+2014%2E+Doubly+robust+policy+evaluation+and+optimization%2E+Statistical+Science%2C+29%284%29%3A485%E2%80%93511%2E)
34. Siqi Fan, Xiusheng Huang, Yiqun Yao, Xuezhi Fang, Kang Liu, Peng Han, Shuo Shang, Aixin Sun, and Yequan Wang. 2025. [If an LLM were a character, would it know its own story? evaluating lifelong learning in llms](https://md.research.elamur.ai/free/en/papers/fan-2026-if-llm-were-character-would/). CoRR, abs/2503.23514.
35. Aleksandr Chuklin, Ilya Markov, and Maarten de Rijke. 2015. Click Models for Web Search. Synthesis Lectures on Information Concepts, Retrieval, and Services. Morgan & Claypool Publishers. [find](https://scholar.google.com/scholar?q=Aleksandr+Chuklin%2C+Ilya+Markov%2C+and+Maarten+de+Rijke%2E+2015%2E+Click+Models+for+Web+Search%2E+Synthesis+Lectures+on+Information+Concepts%2C+Retrieval%2C+and+Services%2E+Morgan+%26+Claypool+Publishers%2E)
36. Neil M. Ferguson, Derek A.T. Cummings, Christophe Fraser, James C. Cajka, Patrick C. Cooley, and Donald S. Burke. 2006. Strategies for mitigating an influenza pandemic. Nature, 442(7101):448–452. [find](https://scholar.google.com/scholar?q=Neil+M%2E+Ferguson%2C+Derek+A%2ET%2E+Cummings%2C+Christophe+Fraser%2C+James+C%2E+Cajka%2C+Patrick+C%2E+Cooley%2C+and+Donald+S%2E+Burke%2E+2006%2E+Strategies+for+mitigating+an+influenza+pandemic%2E+Nature%2C+442%287101%29%3A448%E2%80%93452%2E)
37. Nick Craswell, Onno Zoeter, Michael J. Taylor, and Bill Ramsey. 2008. An experimental comparison of click position-bias models. In Proceedings of the International Conference on Web Search and Web Data Mining, WSDM 2008, pages 87–94. ACM. [find](https://scholar.google.com/scholar?q=Nick+Craswell%2C+Onno+Zoeter%2C+Michael+J%2E+Taylor%2C+and+Bill+Ramsey%2E+2008%2E+An+experimental+comparison+of+click+position%2Dbias+models%2E+In+Proceedings+of+the+International+Conference+on+Web+Search+and+Web+Dat)
38. W. Tecumseh Fitch, Ludwig Huber, and Thomas Bugn-yar. 2010. Social cognition and the evolution of language: constructing cognitive phylogenies. Neuron, 65(6):795–814. [find](https://scholar.google.com/scholar?q=W%2E+Tecumseh+Fitch%2C+Ludwig+Huber%2C+and+Thomas+Bugn%2Dyar%2E+2010%2E+Social+cognition+and+the+evolution+of+language%3A+constructing+cognitive+phylogenies%2E+Neuron%2C+65%286%29%3A795%E2%80%93814%2E)
39. Robert H. Crites and Andrew G. Barto. 1995. Improving elevator performance using reinforcement learning. In Advances in Neural Information Processing Systems 8, NeurIPS 1995, pages 1017–1023. MIT Press. [find](https://scholar.google.com/scholar?q=Robert+H%2E+Crites+and+Andrew+G%2E+Barto%2E+1995%2E+Improving+elevator+performance+using+reinforcement+learning%2E+In+Advances+in+Neural+Information+Processing+Systems+8%2C+NeurIPS+1995%2C+pages+1017%E2%80%931023%2E+MIT+Pres)
40. Simon Frieder, Luca Pinchetti, Alexis Chevalier, Ryan-Rhys Griffiths, Tommaso Salvatori, Thomas Lukasiewicz, Philipp Petersen, and Julius Berner. 2023. [Mathematical capabilities of chatgpt](https://md.research.elamur.ai/free/en/papers/frieder-2023-mathematical-capabilities-chatgpt/). In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Sy…
41. Trisha Das, Dina Albassam, and Jimeng Sun. 2024. Synthetic patient-physician dialogue generation from clinical notes using LLM. CoRR, abs/2408.06285. — [arXiv:2408.06285](https://arxiv.org/abs/2408.06285) [find](https://scholar.google.com/scholar?q=Trisha+Das%2C+Dina+Albassam%2C+and+Jimeng+Sun%2E+2024%2E+Synthetic+patient%2Dphysician+dialogue+generation+from+clinical+notes+using+LLM%2E+CoRR%2C+abs%2F2408%2E06285%2E+%E2%80%94+%5BarXiv%3A2408%2E06285%5D%28https%3A%2F%2Farxiv%2Eorg%2Fabs%2F2408%2E06)
42. Jingsheng Gao, Yixin Lian, Ziyi Zhou, Yuzhuo Fu, and Baoyuan Wang. 2023. Livechat: A large-scale personalized dialogue dataset automatically constructed from live streaming. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2023,… [find](https://scholar.google.com/scholar?q=Jingsheng+Gao%2C+Yixin+Lian%2C+Ziyi+Zhou%2C+Yuzhuo+Fu%2C+and+Baoyuan+Wang%2E+2023%2E+Livechat%3A+A+large%2Dscale+personalized+dialogue+dataset+automatically+constructed+from+live+streaming%2E+In+Proceedings+of+the+61st)
43. Jiawei Gu, Xuhui Jiang, Zhichao Shi, Hexiang Tan, Xuehao Zhai, Chengjin Xu, Wei Li, Yinghan Shen, Shengjie Ma, Honghao Liu, Saizhuo Wang, Kun Zhang, Yuanzhuo Wang, Wen Gao, Lionel Ni, and Jian Guo. 2025. A survey on llm-as-a-judge. [find](https://scholar.google.com/scholar?q=Jiawei+Gu%2C+Xuhui+Jiang%2C+Zhichao+Shi%2C+Hexiang+Tan%2C+Xuehao+Zhai%2C+Chengjin+Xu%2C+Wei+Li%2C+Yinghan+Shen%2C+Shengjie+Ma%2C+Honghao+Liu%2C+Saizhuo+Wang%2C+Kun+Zhang%2C+Yuanzhuo+Wang%2C+Wen+Gao%2C+Lionel+Ni%2C+and+Jian+Guo%2E+20)
44. Jiawei Gu, Xuhui Jiang, Zhichao Shi, Hexiang Tan, Xuehao Zhai, Chengjin Xu, Wei Li, Yinghan Shen, Shengjie Ma, Honghao Liu, Yuanzhuo Wang, and Jian Guo. 2024. A survey on llm-as-a-judge. CoRR, abs/2411.15594. [find](https://scholar.google.com/scholar?q=Jiawei+Gu%2C+Xuhui+Jiang%2C+Zhichao+Shi%2C+Hexiang+Tan%2C+Xuehao+Zhai%2C+Chengjin+Xu%2C+Wei+Li%2C+Yinghan+Shen%2C+Shengjie+Ma%2C+Honghao+Liu%2C+Yuanzhuo+Wang%2C+and+Jian+Guo%2E+2024%2E+A+survey+on+llm%2Das%2Da%2Djudge%2E+CoRR%2C+abs%2F241)
45. Taicheng Guo, Xiuying Chen, Yaqi Wang, Ruidi Chang, Shichao Pei, Nitesh V. Chawla, Olaf Wiest, and Xiangliang Zhang. 2024. [Large language model based multi-agents: A survey of progress and challenges](https://md.research.elamur.ai/free/en/papers/guo-2024-large-language-model-based/). In Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI…
46. Jennifer Haase and Sebastian Pokutta. 2025. Beyond static responses: Multi-agent LLM systems as a new paradigm for social science research. CoRR, abs/2506.01839. — [arXiv:2506.01839](https://arxiv.org/abs/2506.01839) [find](https://scholar.google.com/scholar?q=Jennifer+Haase+and+Sebastian+Pokutta%2E+2025%2E+Beyond+static+responses%3A+Multi%2Dagent+LLM+systems+as+a+new+paradigm+for+social+science+research%2E+CoRR%2C+abs%2F2506%2E01839%2E+%E2%80%94+%5BarXiv%3A2506%2E01839%5D%28https%3A%2F%2Farxiv%2Eorg)
47. Perttu Hämäläinen, Mikke Tavast, and Anton Kunnari. 2023. Evaluating large language models in generating synthetic HCI research data: a case study. In Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems, CHI 2023, pages 433:1–433:19. ACM. [find](https://scholar.google.com/scholar?q=Perttu+H%C3%A4m%C3%A4l%C3%A4inen%2C+Mikke+Tavast%2C+and+Anton+Kunnari%2E+2023%2E+Evaluating+large+language+models+in+generating+synthetic+HCI+research+data%3A+a+case+study%2E+In+Proceedings+of+the+2023+CHI+Conference+on+Human+F)
48. F. Maxwell Harper and Joseph A. Konstan. 2015. The movielens datasets: History and context. ACM Transactions on Interactive Intelligent Systems, 5(4):1–19. [find](https://scholar.google.com/scholar?q=F%2E+Maxwell+Harper+and+Joseph+A%2E+Konstan%2E+2015%2E+The+movielens+datasets%3A+History+and+context%2E+ACM+Transactions+on+Interactive+Intelligent+Systems%2C+5%284%29%3A1%E2%80%9319%2E)
49. Naieme Hazrati and Francesco Ricci. 2022. Simulating users’ interactions with recommender systems. In UMAP ’22: 30th ACM Conference on User Modeling, Adaptation and Personalization, pages 95–98. ACM. [find](https://scholar.google.com/scholar?q=Naieme+Hazrati+and+Francesco+Ricci%2E+2022%2E+Simulating+users%E2%80%99+interactions+with+recommender+systems%2E+In+UMAP+%E2%80%9922%3A+30th+ACM+Conference+on+User+Modeling%2C+Adaptation+and+Personalization%2C+pages+95%E2%80%9398%2E+ACM%2E)
50. He He, Derek Chen, Anusha Balakrishnan, and Percy Liang. 2018. [Decoupling strategy and generation in negotiation dialogues](https://md.research.elamur.ai/free/en/papers/he-2018-decoupling-strategy-generation-negotiation-dialogues/). In Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing, pages 2333–2343. Association for Computational Linguistics.
51. Sviatlana Höhn, Jauwairia Nasir, Daniel C. Tozadore, Ali Paikan, Pouyan Ziafati, and Elisabeth André. 2024. Beyond pretend-reality dualism: Frame analysis of llm-powered role play with social agents. In Proceedings of the 12th International Conference on Human-Agent Interaction, HAI 2024, pages 393–… [find](https://scholar.google.com/scholar?q=Sviatlana+H%C3%B6hn%2C+Jauwairia+Nasir%2C+Daniel+C%2E+Tozadore%2C+Ali+Paikan%2C+Pouyan+Ziafati%2C+and+Elisabeth+Andr%C3%A9%2E+2024%2E+Beyond+pretend%2Dreality+dualism%3A+Frame+analysis+of+llm%2Dpowered+role+play+with+social+agents%2E+)
52. Joey Hong, Jessica Lin, Anca D. Dragan, and Sergey Levine. 2024. Interactive dialogue agents via reinforcement learning on hindsight regenerations. CoRR, abs/2411.05194. — [arXiv:2411.05194](https://arxiv.org/abs/2411.05194) [find](https://scholar.google.com/scholar?q=Joey+Hong%2C+Jessica+Lin%2C+Anca+D%2E+Dragan%2C+and+Sergey+Levine%2E+2024%2E+Interactive+dialogue+agents+via+reinforcement+learning+on+hindsight+regenerations%2E+CoRR%2C+abs%2F2411%2E05194%2E+%E2%80%94+%5BarXiv%3A2411%2E05194%5D%28https%3A%2F%2Fa)
53. Daniel G. Horvitz and Donovan J. Thompson. 1952. A generalization of sampling without replacement from a finite universe. Journal of the American Statistical Association, 47(260):663–685. [find](https://scholar.google.com/scholar?q=Daniel+G%2E+Horvitz+and+Donovan+J%2E+Thompson%2E+1952%2E+A+generalization+of+sampling+without+replacement+from+a+finite+universe%2E+Journal+of+the+American+Statistical+Association%2C+47%28260%29%3A663%E2%80%93685%2E)
54. Tiancheng Hu and Nigel Collier. 2024. [Quantifying the persona effect in LLM simulations](https://md.research.elamur.ai/free/en/papers/hu-2024-quantifying-persona-effect-llm-simulations/). In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2024, pages 10289–10307. Association for Computational Linguistics.
55. Zhiyuan Hu, Yue Feng, Anh Tuan Luu, Bryan Hooi, and Aldo Lipani. 2023. Unlocking the potential of user feedback: Leveraging large language model as user simulators to enhance dialogue system. In Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, CIKM 2023,… [find](https://scholar.google.com/scholar?q=Zhiyuan+Hu%2C+Yue+Feng%2C+Anh+Tuan+Luu%2C+Bryan+Hooi%2C+and+Aldo+Lipani%2E+2023%2E+Unlocking+the+potential+of+user+feedback%3A+Leveraging+large+language+model+as+user+simulators+to+enhance+dialogue+system%2E+In+Proce)
56. Wenyue Hua, Ollie Liu, Lingyao Li, Alfonso Amayuelas, Julie Chen, Lucas Jiang, Mingyu Jin, Lizhou Fan, Fei Sun, William Wang, Xintong Wang, and Yongfeng Zhang. 2024. Game-theoretic LLM: agent workflow for negotiation games. CoRR, abs/2411.05990. — [arXiv:2411.05990](https://arxiv.org/abs/2411.05990) [find](https://scholar.google.com/scholar?q=Wenyue+Hua%2C+Ollie+Liu%2C+Lingyao+Li%2C+Alfonso+Amayuelas%2C+Julie+Chen%2C+Lucas+Jiang%2C+Mingyu+Jin%2C+Lizhou+Fan%2C+Fei+Sun%2C+William+Wang%2C+Xintong+Wang%2C+and+Yongfeng+Zhang%2E+2024%2E+Game%2Dtheoretic+LLM%3A+agent+workflow)
57. Yuxuan Huang. 2024. Orca: Enhancing role-playing abilities of large language models by integrating personality traits. CoRR, abs/2411.10006. — [arXiv:2411.10006](https://arxiv.org/abs/2411.10006) [find](https://scholar.google.com/scholar?q=Yuxuan+Huang%2E+2024%2E+Orca%3A+Enhancing+role%2Dplaying+abilities+of+large+language+models+by+integrating+personality+traits%2E+CoRR%2C+abs%2F2411%2E10006%2E+%E2%80%94+%5BarXiv%3A2411%2E10006%5D%28https%3A%2F%2Farxiv%2Eorg%2Fabs%2F2411%2E10006%29)
58. Eugene Ie, Chih-Wei Hsu, Martin Mladenov, Vihan Jain, Sanmit Narvekar, Jing Wang, Rui Wu, and Craig Boutilier. 2019. Recsim: A configurable simulation platform for recommender systems. CoRR, abs/1909.04847. — [arXiv:1909.04847](https://arxiv.org/abs/1909.04847) [find](https://scholar.google.com/scholar?q=Eugene+Ie%2C+Chih%2DWei+Hsu%2C+Martin+Mladenov%2C+Vihan+Jain%2C+Sanmit+Narvekar%2C+Jing+Wang%2C+Rui+Wu%2C+and+Craig+Boutilier%2E+2019%2E+Recsim%3A+A+configurable+simulation+platform+for+recommender+systems%2E+CoRR%2C+abs%2F1909%2E)
59. Edward Ionides. 2008. Truncated importance sampling. Journal of Computational and Graphical Statistics, 17(2):295–311. [find](https://scholar.google.com/scholar?q=Edward+Ionides%2E+2008%2E+Truncated+importance+sampling%2E+Journal+of+Computational+and+Graphical+Statistics%2C+17%282%29%3A295%E2%80%93311%2E)
60. Yoonna Jang, Jungwoo Lim, Yuna Hur, Dongsuk Oh, Suhyune Son, Yeonsoo Lee, Dong-Hoon Shin, Seungryong Kim, and Heuiseok Lim. 2022. Call for customized conversation: Customized conversation grounding persona and knowledge. In Proceedings of the Thirty-Sixth AAAI Conference on Artificial Intelligence,… [find](https://scholar.google.com/scholar?q=Yoonna+Jang%2C+Jungwoo+Lim%2C+Yuna+Hur%2C+Dongsuk+Oh%2C+Suhyune+Son%2C+Yeonsoo+Lee%2C+Dong%2DHoon+Shin%2C+Seungryong+Kim%2C+and+Heuiseok+Lim%2E+2022%2E+Call+for+customized+conversation%3A+Customized+conversation+grounding+pe)
61. Ke Ji, Yixin Lian, Linxu Li, Jingsheng Gao, Weiyuan Li, and Bin Dai. 2025. Enhancing persona consistency for llms’ role-playing using persona-aware contrastive learning. CoRR, abs/2503.17662. [find](https://scholar.google.com/scholar?q=Ke+Ji%2C+Yixin+Lian%2C+Linxu+Li%2C+Jingsheng+Gao%2C+Weiyuan+Li%2C+and+Bin+Dai%2E+2025%2E+Enhancing+persona+consistency+for+llms%E2%80%99+role%2Dplaying+using+persona%2Daware+contrastive+learning%2E+CoRR%2C+abs%2F2503%2E17662%2E)
62. Yongyi Ji, Zhisheng Tang, and Mayank Kejriwal. 2024. Is persona enough for personality? using chatgpt to reconstruct an agent’s latent personality from simple descriptions. In Proceedings of the 41st International Conference on Machine Learning, ICML 2024 Workshop on LLMs and Cognition, volume 235.… [find](https://scholar.google.com/scholar?q=Yongyi+Ji%2C+Zhisheng+Tang%2C+and+Mayank+Kejriwal%2E+2024%2E+Is+persona+enough+for+personality%3F+using+chatgpt+to+reconstruct+an+agent%E2%80%99s+latent+personality+from+simple+descriptions%2E+In+Proceedings+of+the+41st+)
63. Guangyuan Jiang, Manjie Xu, Song-Chun Zhu, Wenjuan Han, Chi Zhang, and Yixin Zhu. 2023. Evaluating and inducing personality in pre-trained language models. In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 2023. [find](https://scholar.google.com/scholar?q=Guangyuan+Jiang%2C+Manjie+Xu%2C+Song%2DChun+Zhu%2C+Wenjuan+Han%2C+Chi+Zhang%2C+and+Yixin+Zhu%2E+2023%2E+Evaluating+and+inducing+personality+in+pre%2Dtrained+language+models%2E+In+Advances+in+Neural+Information+Processing)
64. Hang Jiang, Xiajie Zhang, Xubo Cao, Cynthia Breazeal, Deb Roy, and Jad Kabbara. 2024. Personallm: Investigating the ability of large language models to express personality traits. In Findings of the Association for Computational Linguistics: NAACL 2024, pages 3605–3627. Association for Computational… [find](https://scholar.google.com/scholar?q=Hang+Jiang%2C+Xiajie+Zhang%2C+Xubo+Cao%2C+Cynthia+Breazeal%2C+Deb+Roy%2C+and+Jad+Kabbara%2E+2024%2E+Personallm%3A+Investigating+the+ability+of+large+language+models+to+express+personality+traits%2E+In+Findings+of+the+A)
65. Hyoungwook Jin, Minju Yoo, Jeongeon Park, Yokyung Lee, Xu Wang, and Juho Kim. 2025. Teachtune: Reviewing pedagogical agents against diverse student profiles with simulated students. In Proceedings of the 2025 CHI Conference on Human Factors in Computing Systems, CHI 2025, pages 1073:1–1073:28. ACM. [find](https://scholar.google.com/scholar?q=Hyoungwook+Jin%2C+Minju+Yoo%2C+Jeongeon+Park%2C+Yokyung+Lee%2C+Xu+Wang%2C+and+Juho+Kim%2E+2025%2E+Teachtune%3A+Reviewing+pedagogical+agents+against+diverse+student+profiles+with+simulated+students%2E+In+Proceedings+of+)
66. Thorsten Joachims, Adith Swaminathan, and Tobias Schnabel. 2017. Unbiased learning-to-rank with biased feedback. In Proceedings of the Tenth ACM International Conference on Web Search and Data Mining, WSDM 2017, pages 781–789. ACM. [find](https://scholar.google.com/scholar?q=Thorsten+Joachims%2C+Adith+Swaminathan%2C+and+Tobias+Schnabel%2E+2017%2E+Unbiased+learning%2Dto%2Drank+with+biased+feedback%2E+In+Proceedings+of+the+Tenth+ACM+International+Conference+on+Web+Search+and+Data+Mining%2C)
67. Brihi Joshi, Xiang Ren, Swabha Swayamdipta, Rik Koncel-Kedziorski, and Tim Paek. 2025. Improving language model personas via rationalization with psychological scaffolds. CoRR, abs/2504.17993. [find](https://scholar.google.com/scholar?q=Brihi+Joshi%2C+Xiang+Ren%2C+Swabha+Swayamdipta%2C+Rik+Koncel%2DKedziorski%2C+and+Tim+Paek%2E+2025%2E+Improving+language+model+personas+via+rationalization+with+psychological+scaffolds%2E+CoRR%2C+abs%2F2504%2E17993%2E)
68. Magdalena Kaiser and Gerhard Weikum. 2025. Preference-based learning with retrieval augmented generation for conversational question answering. In Companion Proceedings of the ACM on Web Conference 2025, WWW 2025, pages 1053–1057. ACM. [find](https://scholar.google.com/scholar?q=Magdalena+Kaiser+and+Gerhard+Weikum%2E+2025%2E+Preference%2Dbased+learning+with+retrieval+augmented+generation+for+conversational+question+answering%2E+In+Companion+Proceedings+of+the+ACM+on+Web+Conference+20)
69. Kate Kaplan. 2020. Typical designer–to–developer and researcher–to–designer ratios. [find](https://scholar.google.com/scholar?q=Kate+Kaplan%2E+2020%2E+Typical+designer%E2%80%93to%E2%80%93developer+and+researcher%E2%80%93to%E2%80%93designer+ratios%2E)
70. David Kempe, Jon M. Kleinberg, and Éva Tardos. 2003. Maximizing the spread of influence through a social network. In Proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pages 137–146. ACM. [find](https://scholar.google.com/scholar?q=David+Kempe%2C+Jon+M%2E+Kleinberg%2C+and+%C3%89va+Tardos%2E+2003%2E+Maximizing+the+spread+of+influence+through+a+social+network%2E+In+Proceedings+of+the+Ninth+ACM+SIGKDD+International+Conference+on+Knowledge+Discovery)
71. Johannes Kiesel, Marcel Gohsen, Nailia Mirzakhme-dova, Matthias Hagen, and Benno Stein. 2024. Simulating follow-up questions in conversational search. In Advances in Information Retrieval - 46th European Conference on Information Retrieval, ECIR 2024, volume 14609 of Lecture Notes in Computer Scienc… [find](https://scholar.google.com/scholar?q=Johannes+Kiesel%2C+Marcel+Gohsen%2C+Nailia+Mirzakhme%2Ddova%2C+Matthias+Hagen%2C+and+Benno+Stein%2E+2024%2E+Simulating+follow%2Dup+questions+in+conversational+search%2E+In+Advances+in+Information+Retrieval+%2D+46th+Europ)
72. Benjamin Klieger, Charis Charitsis, Miroslav Suzara, Sierra Wang, Nick Haber, and John C. Mitchell. 2024. Chatcollab: Exploring collaboration between humans and AI agents in software teams. CoRR, abs/2412.01992. — [arXiv:2412.01992](https://arxiv.org/abs/2412.01992) [find](https://scholar.google.com/scholar?q=Benjamin+Klieger%2C+Charis+Charitsis%2C+Miroslav+Suzara%2C+Sierra+Wang%2C+Nick+Haber%2C+and+John+C%2E+Mitchell%2E+2024%2E+Chatcollab%3A+Exploring+collaboration+between+humans+and+AI+agents+in+software+teams%2E+CoRR%2C+abs%2F)
73. Aobo Kong, Wentao Ma, Shiwan Zhao, Yongbin Li, Yuchuan Wu, Ke Wang, Xiaoqian Liu, Qicheng Li, Yong Qin, and Fei Huang. 2025. SDPO: segment-level direct preference optimization for social agents. CoRR, abs/2501.01821. [find](https://scholar.google.com/scholar?q=Aobo+Kong%2C+Wentao+Ma%2C+Shiwan+Zhao%2C+Yongbin+Li%2C+Yuchuan+Wu%2C+Ke+Wang%2C+Xiaoqian+Liu%2C+Qicheng+Li%2C+Yong+Qin%2C+and+Fei+Huang%2E+2025%2E+SDPO%3A+segment%2Dlevel+direct+preference+optimization+for+social+agents%2E+CoRR%2C)
74. Chuyi Kong, Yaxin Fan, Xiang Wan, Feng Jiang, and Benyou Wang. 2024. Platolm: Teaching llms in multi-round dialogue via a user simulator. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2024, pages 7841–7863. Association for Com… [find](https://scholar.google.com/scholar?q=Chuyi+Kong%2C+Yaxin+Fan%2C+Xiang+Wan%2C+Feng+Jiang%2C+and+Benyou+Wang%2E+2024%2E+Platolm%3A+Teaching+llms+in+multi%2Dround+dialogue+via+a+user+simulator%2E+In+Proceedings+of+the+62nd+Annual+Meeting+of+the+Association+f)
75. Yehuda Koren, Robert M. Bell, and Chris Volinsky. 2009. Matrix factorization techniques for recommender systems. IEEE Computer, 42(8):30–37. [find](https://scholar.google.com/scholar?q=Yehuda+Koren%2C+Robert+M%2E+Bell%2C+and+Chris+Volinsky%2E+2009%2E+Matrix+factorization+techniques+for+recommender+systems%2E+IEEE+Computer%2C+42%288%29%3A30%E2%80%9337%2E)
76. Branislav Kveton, Csaba Szepesvári, Zheng Wen, and Azin Ashkan. 2015. Cascading bandits: Learning to rank in the cascade model. In Proceedings of the 32nd International Conference on Machine Learning, ICML 2015, volume 37 of JMLR Workshop and Conference Proceedings, pages 767–776. [find](https://scholar.google.com/scholar?q=Branislav+Kveton%2C+Csaba+Szepesv%C3%A1ri%2C+Zheng+Wen%2C+and+Azin+Ashkan%2E+2015%2E+Cascading+bandits%3A+Learning+to+rank+in+the+cascade+model%2E+In+Proceedings+of+the+32nd+International+Conference+on+Machine+Learning%2C)
77. Philippe Laban, Hiroaki Hayashi, Yingbo Zhou, and Jennifer Neville. 2025. [Llms get lost in multi-turn conversation](https://md.research.elamur.ai/free/en/papers/laban-2025-llms-get-lost-multi-turn/).
78. Paul Lagrée, Claire Vernade, and Olivier Cappé. 2016. Multiple-play bandits in the position-based model. In Advances in Neural Information Processing Systems 29: Annual Conference on Neural Information Processing Systems 2016, NeurIPS 2016, pages 1597– 1605. [find](https://scholar.google.com/scholar?q=Paul+Lagr%C3%A9e%2C+Claire+Vernade%2C+and+Olivier+Capp%C3%A9%2E+2016%2E+Multiple%2Dplay+bandits+in+the+position%2Dbased+model%2E+In+Advances+in+Neural+Information+Processing+Systems+29%3A+Annual+Conference+on+Neural+Informatio)
79. Luc Lamontagne, François Laviolette, Richard Khoury, and Alexandre Bergeron-Guyard. 2014. A framework for building adaptive intelligent virtual assistants. In Artificial intelligence and applications, volume 10, pages 2014–816. [find](https://scholar.google.com/scholar?q=Luc+Lamontagne%2C+Fran%C3%A7ois+Laviolette%2C+Richard+Khoury%2C+and+Alexandre+Bergeron%2DGuyard%2E+2014%2E+A+framework+for+building+adaptive+intelligent+virtual+assistants%2E+In+Artificial+intelligence+and+applications%2C)
80. Jeongmin Lee, Jin-Xia Huang, Minsoo Cho, Yoon-Hyung Roh, Oh-Woog Kwon, and Yunkeun Lee. 2024. Developing conversational intelligent tutoring for speaking skills in second language learning. In Generative Intelligence and Intelligent Tutoring Systems - 20th International Conference, ITS 2024, volume… [find](https://scholar.google.com/scholar?q=Jeongmin+Lee%2C+Jin%2DXia+Huang%2C+Minsoo+Cho%2C+Yoon%2DHyung+Roh%2C+Oh%2DWoog+Kwon%2C+and+Yunkeun+Lee%2E+2024%2E+Developing+conversational+intelligent+tutoring+for+speaking+skills+in+second+language+learning%2E+In+Generat)
81. Joanne Leong, John C. Tang, Edward Cutrell, Sasa Junuzovic, Gregory Paul Baribault, and Kori Inkpen. 2024. Dittos: Personalized, embodied agents that participate in meetings when you are unavailable. Proceedings of the ACM on Human-Computer Interaction, 8(CSCW2):1–28. [find](https://scholar.google.com/scholar?q=Joanne+Leong%2C+John+C%2E+Tang%2C+Edward+Cutrell%2C+Sasa+Junuzovic%2C+Gregory+Paul+Baribault%2C+and+Kori+Inkpen%2E+2024%2E+Dittos%3A+Personalized%2C+embodied+agents+that+participate+in+meetings+when+you+are+unavailable%2E+)
82. Mike Lewis, Denis Yarats, Yann N. Dauphin, Devi Parikh, and Dhruv Batra. 2017. Deal or no deal? end-to-end learning for negotiation dialogues. CoRR, abs/1706.05125. — [arXiv:1706.05125](https://arxiv.org/abs/1706.05125) [find](https://scholar.google.com/scholar?q=Mike+Lewis%2C+Denis+Yarats%2C+Yann+N%2E+Dauphin%2C+Devi+Parikh%2C+and+Dhruv+Batra%2E+2017%2E+Deal+or+no+deal%3F+end%2Dto%2Dend+learning+for+negotiation+dialogues%2E+CoRR%2C+abs%2F1706%2E05125%2E+%E2%80%94+%5BarXiv%3A1706%2E05125%5D%28https%3A%2F%2Farxiv%2E)
83. Patrick Lewis, Ethan Perez, Aleksandra Piktus, Fabio Petroni, Vladimir Karpukhin, Naman Goyal, Heinrich Küttler, Mike Lewis, Wen-tau Yih, Tim Rocktäschel, Sebastian Riedel, and Douwe Kiela. 2020. [Retrieval-augmented generation for knowledge-intensive NLP tasks](https://md.research.elamur.ai/free/en/papers/lewis-2020-retrieval-augmented-generation-knowledge-intensive/). In Advances in Neural Information Proc…
84. Ang Li, Haozhe Chen, Hongseok Namkoong, and Tianyi Peng. 2025a. LLM generated persona is a promise with a catch. CoRR, abs/2503.16527. — [arXiv:2503.16527](https://arxiv.org/abs/2503.16527) [find](https://scholar.google.com/scholar?q=Ang+Li%2C+Haozhe+Chen%2C+Hongseok+Namkoong%2C+and+Tianyi+Peng%2E+2025a%2E+LLM+generated+persona+is+a+promise+with+a+catch%2E+CoRR%2C+abs%2F2503%2E16527%2E+%E2%80%94+%5BarXiv%3A2503%2E16527%5D%28https%3A%2F%2Farxiv%2Eorg%2Fabs%2F2503%2E16527%29)
85. Guohao Li, Hasan Hammoud, Hani Itani, Dmitrii Khizbullin, and Bernard Ghanem. 2023. [CAMEL: communicative agents for "mind" exploration of large language model society](https://md.research.elamur.ai/free/en/papers/li-2023-camel-communicative-agents-mind/). In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, NeurIPS 20…
86. Haitao Li, Qian Dong, Junjie Chen, Huixue Su, Yujia Zhou, Qingyao Ai, Ziyi Ye, and Yiqun Liu. 2024a. [Llms-as-judges: A comprehensive survey on llm-based evaluation methods](https://md.research.elamur.ai/free/en/papers/li-2024-llms-judges-comprehensive-survey-llm/).
87. Haoran Li, Qingxiu Dong, Zhengyang Tang, Chaojun Wang, Xingxing Zhang, Haoyang Huang, Shaohan Huang, Xiaolong Huang, Zeqiang Huang, Dongdong Zhang, Yuxian Gu, Xin Cheng, Xun Wang, Si-Qing Chen, Li Dong, Wei Lu, Zhifang Sui, Benyou Wang, Wai Lam, and Furu Wei. 2024b. Synthetic data (almost) from scra… [find](https://scholar.google.com/scholar?q=Haoran+Li%2C+Qingxiu+Dong%2C+Zhengyang+Tang%2C+Chaojun+Wang%2C+Xingxing+Zhang%2C+Haoyang+Huang%2C+Shaohan+Huang%2C+Xiaolong+Huang%2C+Zeqiang+Huang%2C+Dongdong+Zhang%2C+Yuxian+Gu%2C+Xin+Cheng%2C+Xun+Wang%2C+Si%2DQing+Chen%2C+Li+Don)
88. Jiwei Li, Michel Galley, Chris Brockett, Georgios P. Spithourakis, Jianfeng Gao, and William B. Dolan. 2016. [A persona-based neural conversation model](https://md.research.elamur.ai/free/en/papers/li-2016-persona-based-neural-conversation-model/). In Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics, ACL 2016. The Association for Computer Linguistics.
89. Juntao Li, Chang Liu, Chongyang Tao, Zhangming Chan, Dongyan Zhao, Min Zhang, and Rui Yan. 2021. Dialogue history matters! personalized response selection in multi-turn retrieval-based chatbots. ACM Transactions on Information Systems (TOIS), 39(4):45:1–45:25. [find](https://scholar.google.com/scholar?q=Juntao+Li%2C+Chang+Liu%2C+Chongyang+Tao%2C+Zhangming+Chan%2C+Dongyan+Zhao%2C+Min+Zhang%2C+and+Rui+Yan%2E+2021%2E+Dialogue+history+matters%21+personalized+response+selection+in+multi%2Dturn+retrieval%2Dbased+chatbots%2E+ACM+T)
90. Li Li, Peilin Cai, Ryan A. Rossi, Franck Dernoncourt, Branislav Kveton, Junda Wu, Tong Yu, Linxin Song, Tiankai Yang, Yuehan Qin, Nesreen K. Ahmed, Samyadeep Basu, Subhojyoti Mukherjee, Ruiyi Zhang, Zhengmian Hu, Bo Ni, Yuxiao Zhou, Zichao Wang, Yue Huang, Yu Wang, Xiangliang Zhang, Philip S. Yu, Xi… — [arXiv:2505.14106](https://arxiv.org/abs/2505.14106) [find](https://scholar.google.com/scholar?q=Li+Li%2C+Peilin+Cai%2C+Ryan+A%2E+Rossi%2C+Franck+Dernoncourt%2C+Branislav+Kveton%2C+Junda+Wu%2C+Tong+Yu%2C+Linxin+Song%2C+Tiankai+Yang%2C+Yuehan+Qin%2C+Nesreen+K%2E+Ahmed%2C+Samyadeep+Basu%2C+Subhojyoti+Mukherjee%2C+Ruiyi+Zhang%2C+Z)
91. Li Li, Wei Ji, Yiming Wu, Mengze Li, You Qin, Lina Wei, and Roger Zimmermann. 2024c. Panoptic scene graph generation with semantics-prototype learning. In Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, AAAI 2024, pages 3145– 3153. AAAI Press. [find](https://scholar.google.com/scholar?q=Li+Li%2C+Wei+Ji%2C+Yiming+Wu%2C+Mengze+Li%2C+You+Qin%2C+Lina+Wei%2C+and+Roger+Zimmermann%2E+2024c%2E+Panoptic+scene+graph+generation+with+semantics%2Dprototype+learning%2E+In+Proceedings+of+the+Thirty%2DEighth+AAAI+Confere)
92. Shuai Li, Yasin Abbasi-Yadkori, Branislav Kveton, S. Muthukrishnan, Vishwa Vinay, and Zheng Wen. 2018. Offline evaluation of ranking policies with click models. In Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining, KDD 2018, pages 1685– 1694. ACM. [find](https://scholar.google.com/scholar?q=Shuai+Li%2C+Yasin+Abbasi%2DYadkori%2C+Branislav+Kveton%2C+S%2E+Muthukrishnan%2C+Vishwa+Vinay%2C+and+Zheng+Wen%2E+2018%2E+Offline+evaluation+of+ranking+policies+with+click+models%2E+In+Proceedings+of+the+24th+ACM+SIGKDD+I)
93. Jieun Lim, Unggi Lee, Junbo Koh, Yeil Jeong, Yunseo Lee, Gyuri Byun, Haewon Jung, Yoonsun Jang, Sanghyeok Lee, and Jewoong Moon. 2025. Development and implementation of a generative artificial intelligence-enhanced simulation to enhance problem-solving skills for pre-service teachers. Computers & Ed… [find](https://scholar.google.com/scholar?q=Jieun+Lim%2C+Unggi+Lee%2C+Junbo+Koh%2C+Yeil+Jeong%2C+Yunseo+Lee%2C+Gyuri+Byun%2C+Haewon+Jung%2C+Yoonsun+Jang%2C+Sanghyeok+Lee%2C+and+Jewoong+Moon%2E+2025%2E+Development+and+implementation+of+a+generative+artificial+intelli)
94. Chien-Chang Lin, Anna Y. Q. Huang, and Owen H. T. Lu. 2023. Artificial intelligence in intelligent tutoring systems toward sustainable education: a systematic review. Smart Learning Environments, 10(1):41. [find](https://scholar.google.com/scholar?q=Chien%2DChang+Lin%2C+Anna+Y%2E+Q%2E+Huang%2C+and+Owen+H%2E+T%2E+Lu%2E+2023%2E+Artificial+intelligence+in+intelligent+tutoring+systems+toward+sustainable+education%3A+a+systematic+review%2E+Smart+Learning+Environments%2C+10%281)
95. Chin-Yew Lin. 2004. [Rouge: A package for automatic evaluation of summaries](https://md.research.elamur.ai/free/en/papers/lin-2004-rouge-package-automatic-evaluation-summaries/). In Text Summarization Branches Out, pages 74–81. Association for Computational Linguistics.
96. Yen-Ting Lin and Yun-Nung Chen. 2023. [Llm-eval: Unified multi-dimensional automatic evaluation for open-domain conversations with large language models](https://md.research.elamur.ai/free/en/papers/lin-2023-llm-eval-unified-multi-dimensional/).
97. Chang Liu, Xu Tan, Chongyang Tao, Zhenxin Fu, Dongyan Zhao, Tie-Yan Liu, and Rui Yan. 2022. Prophetchat: Enhancing dialogue generation with simulation of future conversation. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2022,… [find](https://scholar.google.com/scholar?q=Chang+Liu%2C+Xu+Tan%2C+Chongyang+Tao%2C+Zhenxin+Fu%2C+Dongyan+Zhao%2C+Tie%2DYan+Liu%2C+and+Rui+Yan%2E+2022%2E+Prophetchat%3A+Enhancing+dialogue+generation+with+simulation+of+future+conversation%2E+In+Proceedings+of+the+60t)
98. Jiahong Liu, Zexuan Qiu, Zhongyang Li, Quanyu Dai, Jieming Zhu, Minda Hu, Menglin Yang, and Irwin King. 2025. A survey of personalized large language models: Progress and future directions. CoRR, abs/2502.11528. — [arXiv:2502.11528](https://arxiv.org/abs/2502.11528) [find](https://scholar.google.com/scholar?q=Jiahong+Liu%2C+Zexuan+Qiu%2C+Zhongyang+Li%2C+Quanyu+Dai%2C+Jieming+Zhu%2C+Minda+Hu%2C+Menglin+Yang%2C+and+Irwin+King%2E+2025%2E+A+survey+of+personalized+large+language+models%3A+Progress+and+future+directions%2E+CoRR%2C+abs%2F)
99. Linyu Liu, Yu Pan, Xiaocheng Li, and Guanting Chen. 2024. Uncertainty estimation and quantification for llms: A simple supervised approach. [find](https://scholar.google.com/scholar?q=Linyu+Liu%2C+Yu+Pan%2C+Xiaocheng+Li%2C+and+Guanting+Chen%2E+2024%2E+Uncertainty+estimation+and+quantification+for+llms%3A+A+simple+supervised+approach%2E)
100. Yajiao Liu, Xin Jiang, Yichun Yin, Yasheng Wang, Fei Mi, Qun Liu, Xiang Wan, and Benyou Wang. 2023. One cannot stand for everyone! leveraging multiple user simulators to train task-oriented dialogue systems. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (… [find](https://scholar.google.com/scholar?q=Yajiao+Liu%2C+Xin+Jiang%2C+Yichun+Yin%2C+Yasheng+Wang%2C+Fei+Mi%2C+Qun+Liu%2C+Xiang+Wan%2C+and+Benyou+Wang%2E+2023%2E+One+cannot+stand+for+everyone%21+leveraging+multiple+user+simulators+to+train+task%2Doriented+dialogue+s)
101. Keming Lu, Bowen Yu, Chang Zhou, and Jingren Zhou. 2024. [Large language models are superpositions of all characters: Attaining arbitrary role-play via self-alignment](https://md.research.elamur.ai/free/en/papers/lu-2024-large-language-models-are-superpositions/). In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2024, pages 7…
102. Xing Han Lù, Amirhossein Kazemnejad, Nicholas Meade, Arkil Patel, Dongchan Shin, Alejandra Zambrano, Karolina Stanczak, Peter Shaw, Christopher J. Pal, and Siva Reddy. 2025. Agentrewardbench: Evaluating automatic evaluations of web agent trajectories. CoRR, abs/2504.08942. — [arXiv:2504.08942](https://arxiv.org/abs/2504.08942) [find](https://scholar.google.com/scholar?q=Xing+Han+L%C3%B9%2C+Amirhossein+Kazemnejad%2C+Nicholas+Meade%2C+Arkil+Patel%2C+Dongchan+Shin%2C+Alejandra+Zambrano%2C+Karolina+Stanczak%2C+Peter+Shaw%2C+Christopher+J%2E+Pal%2C+and+Siva+Reddy%2E+2025%2E+Agentrewardbench%3A+Evaluati)
103. Xiang Luo, Zhiwen Tang, Jin Wang, and Xuejie Zhang. 2024. Duetsim: Building user simulator with dual large language models for task-oriented dialogues. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation, LREC/COLING 2024, pages 5… [find](https://scholar.google.com/scholar?q=Xiang+Luo%2C+Zhiwen+Tang%2C+Jin+Wang%2C+and+Xuejie+Zhang%2E+2024%2E+Duetsim%3A+Building+user+simulator+with+dual+large+language+models+for+task%2Doriented+dialogues%2E+In+Proceedings+of+the+2024+Joint+International+C)
104. Ziyang Luo, Haoning Wu, Dongxu Li, Jing Ma, Mohan S. Kankanhalli, and Junnan Li. 2025. Videoautoarena: An automated arena for evaluating large multimodal models in video analysis through user simulation. In IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2025, pages 8461–8474. C… [find](https://scholar.google.com/scholar?q=Ziyang+Luo%2C+Haoning+Wu%2C+Dongxu+Li%2C+Jing+Ma%2C+Mohan+S%2E+Kankanhalli%2C+and+Junnan+Li%2E+2025%2E+Videoautoarena%3A+An+automated+arena+for+evaluating+large+multimodal+models+in+video+analysis+through+user+simulati)
105. Oleksandr Lytvyn. 2025. Human-ai interaction in language acquisition: Evaluating llm as a language partner. In Proceedings of the MEi: CogSci Conference, volume 19. [find](https://scholar.google.com/scholar?q=Oleksandr+Lytvyn%2E+2025%2E+Human%2Dai+interaction+in+language+acquisition%3A+Evaluating+llm+as+a+language+partner%2E+In+Proceedings+of+the+MEi%3A+CogSci+Conference%2C+volume+19%2E)
106. Navid Madani, Sougata Saha, and Rohini K. Srihari. 2024. Steering conversational large language models for long emotional support conversations. CoRR, abs/2402.10453. [find](https://scholar.google.com/scholar?q=Navid+Madani%2C+Sougata+Saha%2C+and+Rohini+K%2E+Srihari%2E+2024%2E+Steering+conversational+large+language+models+for+long+emotional+support+conversations%2E+CoRR%2C+abs%2F2402%2E10453%2E)
107. Andrea Madotto, Chien-Sheng Wu, and Pascale Fung. 2018. [Mem2seq: Effectively incorporating knowledge bases into end-to-end task-oriented dialog systems](https://md.research.elamur.ai/free/en/papers/madotto-2018-mem2seq-effectively-incorporating-knowledge-bases/). In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, ACL 2018, pages 1468–1478. Association for Computationa…
108. Manqing Mao, Paishun Ting, Yijian Xiang, Mingyang Xu, Julia Chen, and Jianzhe Lin. 2024. Multi-user chat assistant (MUCA): a framework using llms to facilitate group conversations. CoRR, abs/2401.04883. — [arXiv:2401.04883](https://arxiv.org/abs/2401.04883) [find](https://scholar.google.com/scholar?q=Manqing+Mao%2C+Paishun+Ting%2C+Yijian+Xiang%2C+Mingyang+Xu%2C+Julia+Chen%2C+and+Jianzhe+Lin%2E+2024%2E+Multi%2Duser+chat+assistant+%28MUCA%29%3A+a+framework+using+llms+to+facilitate+group+conversations%2E+CoRR%2C+abs%2F2401%2E0488)
109. Shuhaib Mehri, Xiaocheng Yang, Takyoung Kim, Gokhan Tur, Shikib Mehri, and Dilek Hakkani-Tür. 2025. [Goal alignment in llm-based user simulators for conversational ai](https://md.research.elamur.ai/free/en/papers/mehri-2026-goal-alignment-llm-based-user/).
110. Robert J. Moore and Raphael Arar. 2018. Conversational UX design: An introduction. In Robert J. Moore, Margaret H. Szymanski, Raphael Arar, and Guang-Jie Ren, editors, Studies in Conversational UX Design, Human-Computer Interaction Series, pages 1–16. Springer. [find](https://scholar.google.com/scholar?q=Robert+J%2E+Moore+and+Raphael+Arar%2E+2018%2E+Conversational+UX+design%3A+An+introduction%2E+In+Robert+J%2E+Moore%2C+Margaret+H%2E+Szymanski%2C+Raphael+Arar%2C+and+Guang%2DJie+Ren%2C+editors%2C+Studies+in+Conversational+UX+Des)
111. Rémi Munos and Andrew W. Moore. 1999. Variable resolution discretization for high-accuracy solutions of optimal control problems. In Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence, IJCAI 99, pages 1348–1355. Morgan Kaufmann. [find](https://scholar.google.com/scholar?q=R%C3%A9mi+Munos+and+Andrew+W%2E+Moore%2E+1999%2E+Variable+resolution+discretization+for+high%2Daccuracy+solutions+of+optimal+control+problems%2E+In+Proceedings+of+the+Sixteenth+International+Joint+Conference+on+Arti)
112. Bo Ni, Yu Wang, Lu Cheng, Erik Blasch, and Tyler Derr. 2025. Towards trustworthy knowledge graph reasoning: An uncertainty aware perspective. Proceedings of the AAAI Conference on Artificial Intelligence, 39(12):12417–12425. [find](https://scholar.google.com/scholar?q=Bo+Ni%2C+Yu+Wang%2C+Lu+Cheng%2C+Erik+Blasch%2C+and+Tyler+Derr%2E+2025%2E+Towards+trustworthy+knowledge+graph+reasoning%3A+An+uncertainty+aware+perspective%2E+Proceedings+of+the+AAAI+Conference+on+Artificial+Intellige)
113. Monika Ol˛edzka, Mark Benesio Carace, Susana de Oliveira Tomaz, Benny Pan, and Pengfei Jiang. 2024. Ai as a teaching assistant: An innovative approach to education through customized model answer generation and guided practice. Studia Eduka-cyjne, pages 67–79. [find](https://scholar.google.com/scholar?q=Monika+Ol%CB%9Bedzka%2C+Mark+Benesio+Carace%2C+Susana+de+Oliveira+Tomaz%2C+Benny+Pan%2C+and+Pengfei+Jiang%2E+2024%2E+Ai+as+a+teaching+assistant%3A+An+innovative+approach+to+education+through+customized+model+answer+gene)
114. Intergovernmental Panel on Climate Change. 2021. [find](https://scholar.google.com/scholar?q=Intergovernmental+Panel+on+Climate+Change%2E+2021%2E)
115. Climate Change 2021: The Physical Science Basis. Cambridge University Press. [find](https://scholar.google.com/scholar?q=Climate+Change+2021%3A+The+Physical+Science+Basis%2E+Cambridge+University+Press%2E)
116. OpenAI. 2023. [GPT-4 technical report](https://md.research.elamur.ai/free/en/papers/openai-2023-gpt-4-technical-report/). abs/2303.08774.
117. CoRR, Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll L. Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul F. Christiano, Jan Leike, and Ryan Lowe.… — [Training language models to follow instructions with human feedback](https://md.research.elamur.ai/free/en/papers/ouyang-2022-training-language-models-follow-instructions/)
118. Sitong Pan, Robin Schmucker, Bernardo Garcia Bulle Bueno, Salome Aguilar Llanes, Fernanda Albo Alarcón, Hangxiao Zhu, Adam Teo, and Meng Xia. 2025. Tutorup: What if your students were simulated? training tutors to address engagement challenges in online learning. In Proceedings of the 2025 CHI Confe… [find](https://scholar.google.com/scholar?q=Sitong+Pan%2C+Robin+Schmucker%2C+Bernardo+Garcia+Bulle+Bueno%2C+Salome+Aguilar+Llanes%2C+Fernanda+Albo+Alarc%C3%B3n%2C+Hangxiao+Zhu%2C+Adam+Teo%2C+and+Meng+Xia%2E+2025%2E+Tutorup%3A+What+if+your+students+were+simulated%3F+train)
119. Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002. [Bleu: a method for automatic evaluation of machine translation](https://md.research.elamur.ai/free/en/papers/papineni-2002-bleu-method-automatic-evaluation-machine/). In Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics, pages 311–318. ACL.
120. Jaesung Park, Seongeun Yang, Chaewon Yoon, Jongwook Si, Yuchul Jung, and Sungyoung Kim. 2024. Ai english conversation coaching platform in the metaverse: Focused on korean users. In 2024 IEEE 18th International Conference on Application of Information and Communication Technologies (AICT), pages 1–6… [find](https://scholar.google.com/scholar?q=Jaesung+Park%2C+Seongeun+Yang%2C+Chaewon+Yoon%2C+Jongwook+Si%2C+Yuchul+Jung%2C+and+Sungyoung+Kim%2E+2024%2E+Ai+english+conversation+coaching+platform+in+the+metaverse%3A+Focused+on+korean+users%2E+In+2024+IEEE+18th+Int)
121. Joon Sung Park, Joseph C. O’Brien, Carrie Jun Cai, Meredith Ringel Morris, Percy Liang, and Michael S. Bernstein. 2023. Generative agents: Interactive simulacra of human behavior. In Proceedings of the 36th Annual ACM Symposium on User Interface Software and Technology, UIST 2023, pages 2:1–2:22. AC… [find](https://scholar.google.com/scholar?q=Joon+Sung+Park%2C+Joseph+C%2E+O%E2%80%99Brien%2C+Carrie+Jun+Cai%2C+Meredith+Ringel+Morris%2C+Percy+Liang%2C+and+Michael+S%2E+Bernstein%2E+2023%2E+Generative+agents%3A+Interactive+simulacra+of+human+behavior%2E+In+Proceedings+of+th)
122. Ajay Patel, Colin Raffel, and Chris Callison-Burch. 2024. Datadreamer: A tool for synthetic data generation and reproducible LLM workflows. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2024, pages 3781–3799. Association for C… [find](https://scholar.google.com/scholar?q=Ajay+Patel%2C+Colin+Raffel%2C+and+Chris+Callison%2DBurch%2E+2024%2E+Datadreamer%3A+A+tool+for+synthetic+data+generation+and+reproducible+LLM+workflows%2E+In+Proceedings+of+the+62nd+Annual+Meeting+of+the+Association)
123. Nikhil Patel and Sandeep Trivedi. 2020. Leveraging predictive modeling, machine learning personalization, nlp customer support, and ai chatbots to increase customer loyalty. Empirical Quests for Management Essences, 3(3):1–24. [find](https://scholar.google.com/scholar?q=Nikhil+Patel+and+Sandeep+Trivedi%2E+2020%2E+Leveraging+predictive+modeling%2C+machine+learning+personalization%2C+nlp+customer+support%2C+and+ai+chatbots+to+increase+customer+loyalty%2E+Empirical+Quests+for+Manag)
124. Aleksandr V. Petrov, Michael Murtagh, and Karthik Nagesh. 2025. Llms for estimating positional bias in logged interaction data. [find](https://scholar.google.com/scholar?q=Aleksandr+V%2E+Petrov%2C+Michael+Murtagh%2C+and+Karthik+Nagesh%2E+2025%2E+Llms+for+estimating+positional+bias+in+logged+interaction+data%2E)
125. Jinghua Piao, Yuwei Yan, Jun Zhang, Nian Li, Junbo Yan, Xiaochong Lan, Zhihong Lu, Zhiheng Zheng, Jing Yi Wang, Di Zhou, Chen Gao, Fengli Xu, Fang Zhang, Ke Rong, Jun Su, and Yong Li. 2025. Agentsociety: Large-scale simulation of llm-driven generative agents advances understanding of human behaviors… — [arXiv:2502.08691](https://arxiv.org/abs/2502.08691) [find](https://scholar.google.com/scholar?q=Jinghua+Piao%2C+Yuwei+Yan%2C+Jun+Zhang%2C+Nian+Li%2C+Junbo+Yan%2C+Xiaochong+Lan%2C+Zhihong+Lu%2C+Zhiheng+Zheng%2C+Jing+Yi+Wang%2C+Di+Zhou%2C+Chen+Gao%2C+Fengli+Xu%2C+Fang+Zhang%2C+Ke+Rong%2C+Jun+Su%2C+and+Yong+Li%2E+2025%2E+Agentsocie)
126. Robin Lewis Plackett. 1975. The analysis of permutations. Journal of the Royal Statistical Society Series C: Applied Statistics, 24(2):193–202. dataset. In Proceedings of the 57th Conference of the Association for Computational Linguistics, ACL 2019, pages 5370–5381. Association for Computational Li… [find](https://scholar.google.com/scholar?q=Robin+Lewis+Plackett%2E+1975%2E+The+analysis+of+permutations%2E+Journal+of+the+Royal+Statistical+Society+Series+C%3A+Applied+Statistics%2C+24%282%29%3A193%E2%80%93202%2E+dataset%2E+In+Proceedings+of+the+57th+Conference+of+the+As)
127. Ruiyang Ren, Peng Qiu, Yingqi Qu, Jing Liu, Xin Zhao, Hua Wu, Ji-Rong Wen, and Haifeng Wang. 2024a. BASES: large-scale web search user simulation with large language model based agents. In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 902–917. Association for Computati… [find](https://scholar.google.com/scholar?q=Ruiyang+Ren%2C+Peng+Qiu%2C+Yingqi+Qu%2C+Jing+Liu%2C+Xin+Zhao%2C+Hua+Wu%2C+Ji%2DRong+Wen%2C+and+Haifeng+Wang%2E+2024a%2E+BASES%3A+large%2Dscale+web+search+user+simulation+with+large+language+model+based+agents%2E+In+Findings+of)
128. Siyue Ren, Zhiyao Cui, Ruiqi Song, Zhen Wang, and Shuyue Hu. 2024b. Emergence of social norms in generative agent societies: Principles and architecture. In Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, IJCAI 2024, pages 7895–7903. [find](https://scholar.google.com/scholar?q=Siyue+Ren%2C+Zhiyao+Cui%2C+Ruiqi+Song%2C+Zhen+Wang%2C+and+Shuyue+Hu%2E+2024b%2E+Emergence+of+social+norms+in+generative+agent+societies%3A+Principles+and+architecture%2E+In+Proceedings+of+the+Thirty%2DThird+Internation)
129. Pranav Putta, Edmund Mills, Naman Garg, Sumeet Motwani, Chelsea Finn, Divyansh Garg, and Rafael Rafailov. 2024. Agent Q: advanced reasoning and learning for autonomous AI agents. CoRR, abs/2408.07199. [find](https://scholar.google.com/scholar?q=Pranav+Putta%2C+Edmund+Mills%2C+Naman+Garg%2C+Sumeet+Motwani%2C+Chelsea+Finn%2C+Divyansh+Garg%2C+and+Rafael+Rafailov%2E+2024%2E+Agent+Q%3A+advanced+reasoning+and+learning+for+autonomous+AI+agents%2E+CoRR%2C+abs%2F2408%2E07199%2E)
130. Steffen Rendle, Christoph Freudenthaler, Zeno Gantner, and Lars Schmidt-Thieme. 2009. BPR: bayesian personalized ranking from implicit feedback. In UAI 2009, Proceedings of the Twenty-Fifth Conference on Uncertainty in Artificial Intelligence, pages 452–461. AUAI Press. [find](https://scholar.google.com/scholar?q=Steffen+Rendle%2C+Christoph+Freudenthaler%2C+Zeno+Gantner%2C+and+Lars+Schmidt%2DThieme%2E+2009%2E+BPR%3A+bayesian+personalized+ranking+from+implicit+feedback%2E+In+UAI+2009%2C+Proceedings+of+the+Twenty%2DFifth+Conference)
131. Huachuan Qiu, Hongliang He, Shuai Zhang, Anqi Li, and Zhenzhong Lan. 2024. [Smile: Single-turn to multi-turn inclusive language expansion via chatgpt for mental health support](https://md.research.elamur.ai/free/en/papers/qiu-2024-smile-single-turn-multi-turn/). In Findings of the Association for Computational Linguistics: EMNLP 2024, page 615–636. Association for Computational Lingui…
132. Virgile Rennard, Christos Xypolopoulos, and Michalis Vazirgiannis. 2025. Bias in the mirror : Are llms opinions robust to their own adversarial attacks. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2025, pages 2128–2143. Asso… [find](https://scholar.google.com/scholar?q=Virgile+Rennard%2C+Christos+Xypolopoulos%2C+and+Michalis+Vazirgiannis%2E+2025%2E+Bias+in+the+mirror+%3A+Are+llms+opinions+robust+to+their+own+adversarial+attacks%2E+In+Proceedings+of+the+63rd+Annual+Meeting+of+th)
133. Huachuan Qiu and Zhenzhong Lan. 2024. [Interactive agents: Simulating counselor-client psychological counseling via role-playing llm-to-llm interactions](https://md.research.elamur.ai/free/en/papers/qiu-2026-interactive-agents-simulating-counselor-client/).
134. Matthew Richardson, Ewa Dominowska, and Robert Ragno. 2007. Predicting clicks: estimating the clickthrough rate for new ads. In Proceedings of the 16th International Conference on World Wide Web, WWW 2007, pages 521–530. ACM. [find](https://scholar.google.com/scholar?q=Matthew+Richardson%2C+Ewa+Dominowska%2C+and+Robert+Ragno%2E+2007%2E+Predicting+clicks%3A+estimating+the+clickthrough+rate+for+new+ads%2E+In+Proceedings+of+the+16th+International+Conference+on+World+Wide+Web%2C+WWW+)
135. Huachuan Qiu and Zhenzhong Lan. 2025. PsyDial: A large-scale long-term conversational dataset for mental health support. In Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 21624– 21655, Vienna, Austria. Association for Computatio… [find](https://scholar.google.com/scholar?q=Huachuan+Qiu+and+Zhenzhong+Lan%2E+2025%2E+PsyDial%3A+A+large%2Dscale+long%2Dterm+conversational+dataset+for+mental+health+support%2E+In+Proceedings+of+the+63rd+Annual+Meeting+of+the+Association+for+Computational+)
136. Inass Rachidi, Anas Ezzakri, Jaime Bellver-Soler, and Luis Fernando D’Haro. 2025. Design, generation and evaluation of a synthetic dialogue dataset for contextually aware chatbots in art museums. In Proceedings of the 15th International Workshop on Spoken Dialogue Systems Technology, pages 20–28. [find](https://scholar.google.com/scholar?q=Inass+Rachidi%2C+Anas+Ezzakri%2C+Jaime+Bellver%2DSoler%2C+and+Luis+Fernando+D%E2%80%99Haro%2E+2025%2E+Design%2C+generation+and+evaluation+of+a+synthetic+dialogue+dataset+for+contextually+aware+chatbots+in+art+museums%2E+In+P)
137. Rafael Rafailov, Archit Sharma, Eric Mitchell, Christopher D. Manning, Stefano Ermon, and Chelsea Finn. 2023. [Direct preference optimization: Your language model is secretly a reward model](https://md.research.elamur.ai/free/en/papers/rafailov-2023-direct-preference-optimization-language-model/). In Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Sy…
138. Hannah Rashkin, Eric Michael Smith, Margaret Li, and Y-Lan Boureau. 2019. Towards empathetic open-domain conversation models: A new benchmark and James Robins, Andrea Rotnitzky, and Lue Ping Zhao. 1994. Estimation of regression coefficients when some regressors are not always observed. Journal of th… [find](https://scholar.google.com/scholar?q=Hannah+Rashkin%2C+Eric+Michael+Smith%2C+Margaret+Li%2C+and+Y%2DLan+Boureau%2E+2019%2E+Towards+empathetic+open%2Ddomain+conversation+models%3A+A+new+benchmark+and+James+Robins%2C+Andrea+Rotnitzky%2C+and+Lue+Ping+Zhao%2E+199)
139. David Rohde, Stephen Bonner, Travis Dunlop, Flavian Vasile, and Alexandros Karatzoglou. 2018. Reco-gym: A reinforcement learning environment for the problem of product recommendation in online advertising. CoRR, abs/1808.00720. — [arXiv:1808.00720](https://arxiv.org/abs/1808.00720) [find](https://scholar.google.com/scholar?q=David+Rohde%2C+Stephen+Bonner%2C+Travis+Dunlop%2C+Flavian+Vasile%2C+and+Alexandros+Karatzoglou%2E+2018%2E+Reco%2Dgym%3A+A+reinforcement+learning+environment+for+the+problem+of+product+recommendation+in+online+adverti)
140. Jon Saad-Falcon, Omar Khattab, Christopher Potts, and Matei Zaharia. 2024. Ares: An automated evaluation framework for retrieval-augmented generation systems. [find](https://scholar.google.com/scholar?q=Jon+Saad%2DFalcon%2C+Omar+Khattab%2C+Christopher+Potts%2C+and+Matei+Zaharia%2E+2024%2E+Ares%3A+An+automated+evaluation+framework+for+retrieval%2Daugmented+generation+systems%2E)
141. Nafis Sadeq, Zhouhang Xie, Byungkyu Kang, Prarit Lamba, Xiang Gao, and Julian J. McAuley. 2024. Mitigating hallucination in fictional character role-play. In Findings of the Association for Computational Linguistics: EMNLP 2024, pages 14467– 14479. Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Nafis+Sadeq%2C+Zhouhang+Xie%2C+Byungkyu+Kang%2C+Prarit+Lamba%2C+Xiang+Gao%2C+and+Julian+J%2E+McAuley%2E+2024%2E+Mitigating+hallucination+in+fictional+character+role%2Dplay%2E+In+Findings+of+the+Association+for+Computatio)
142. Alireza Salemi, Cheng Li, Mingyang Zhang, Qiaozhu Mei, Weize Kong, Tao Chen, Zhuowan Li, Michael Bendersky, and Hamed Zamani. 2025. Reasoning-enhanced self-training for long-form personalized text generation. [find](https://scholar.google.com/scholar?q=Alireza+Salemi%2C+Cheng+Li%2C+Mingyang+Zhang%2C+Qiaozhu+Mei%2C+Weize+Kong%2C+Tao+Chen%2C+Zhuowan+Li%2C+Michael+Bendersky%2C+and+Hamed+Zamani%2E+2025%2E+Reasoning%2Denhanced+self%2Dtraining+for+long%2Dform+personalized+text+gen)
143. Alireza Salemi, Sheshera Mysore, Michael Bendersky, and Hamed Zamani. 2024. [Lamp: When large language models meet personalization](https://md.research.elamur.ai/free/en/papers/salemi-2024-lamp-when-large-language-models/). In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2024, pages 7370–7392. Association for Computatio…
144. J. Ben Schafer, Dan Frankowski, Jonathan L. Herlocker, and Shilad Sen. 2007. Collaborative filtering recommender systems. In The Adaptive Web: Methods and Strategies of Web Personalization, volume 4321 of Lecture Notes in Computer Science, pages 291–324. Springer. [find](https://scholar.google.com/scholar?q=J%2E+Ben+Schafer%2C+Dan+Frankowski%2C+Jonathan+L%2E+Herlocker%2C+and+Shilad+Sen%2E+2007%2E+Collaborative+filtering+recommender+systems%2E+In+The+Adaptive+Web%3A+Methods+and+Strategies+of+Web+Personalization%2C+volume+432)
145. Ivan Sekulic, Silvia Terragni, Victor Guimarães, Nghia Khau, Bruna Guedes, Modestas Filipavicius, André Ferreira Manso, and Roland Mathis. 2024. Reliable llm-based user simulator for task-oriented dialogue systems. CoRR, abs/2402.13374. [find](https://scholar.google.com/scholar?q=Ivan+Sekulic%2C+Silvia+Terragni%2C+Victor+Guimar%C3%A3es%2C+Nghia+Khau%2C+Bruna+Guedes%2C+Modestas+Filipavicius%2C+Andr%C3%A9+Ferreira+Manso%2C+and+Roland+Mathis%2E+2024%2E+Reliable+llm%2Dbased+user+simulator+for+task%2Doriented+dia)
146. Youngkyung Seo, Yoonseok Heo, Jun-Seok Koh, and Du-Seong Chang. 2024. Efficient and accurate memorable conversation model using DPO based on sllm. CoRR, abs/2407.06537. — [arXiv:2407.06537](https://arxiv.org/abs/2407.06537) [find](https://scholar.google.com/scholar?q=Youngkyung+Seo%2C+Yoonseok+Heo%2C+Jun%2DSeok+Koh%2C+and+Du%2DSeong+Chang%2E+2024%2E+Efficient+and+accurate+memorable+conversation+model+using+DPO+based+on+sllm%2E+CoRR%2C+abs%2F2407%2E06537%2E+%E2%80%94+%5BarXiv%3A2407%2E06537%5D%28https%3A%2F%2Far)
147. Greg Serapio-García, Mustafa Safdari, Clément Crepy, Stephen Fitz, Peter Romero, Luning Sun, Marwa Abdulhai, Aleksandra Faust, and Maja J. Mataric. 2023. [Personality traits in large language models](https://md.research.elamur.ai/free/en/papers/serapio-garcia-2023-personality-traits-large-language-models/). CoRR, abs/2307.00184.
148. Pararth Shah, Dilek Hakkani-Tür, Bing Liu, and Gökhan Tür. 2018. [Bootstrapping a neural conversational agent with dialogue self-play, crowdsourcing and on-line reinforcement learning](https://md.research.elamur.ai/free/en/papers/shah-2018-bootstrapping-neural-conversational-agent-dialogue/). In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics…
149. Murray Shanahan, Kyle McDonell, and Laria Reynolds. 2023. [Role play with large language models](https://md.research.elamur.ai/free/en/papers/shanahan-2023-role-play-large-language-models/). Nature, 623(7987):493–498.
150. Yunfan Shao, Linyang Li, Junqi Dai, and Xipeng Qiu. 2023. [Character-llm: A trainable agent for role-playing](https://md.research.elamur.ai/free/en/papers/shao-2023-character-llm-trainable-agent-role/). In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, pages 13153–13187. Association for Computational Linguistics.
151. Wentao Shi, Mengqi Yuan, Junkang Wu, Qifan Wang, and Fuli Feng. 2024. Direct multi-turn preference optimization for language agents. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024, pages 2312– 2324. Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Wentao+Shi%2C+Mengqi+Yuan%2C+Junkang+Wu%2C+Qifan+Wang%2C+and+Fuli+Feng%2E+2024%2E+Direct+multi%2Dturn+preference+optimization+for+language+agents%2E+In+Proceedings+of+the+2024+Conference+on+Empirical+Methods+in+Natur)
152. Hikaru Shimadzu, Takehito Utsuro, and Daisuke Kitayama. 2025. Retrieval-augmented simulacra: Generative agents for up-to-date and knowledge-adaptive simulations. CoRR, abs/2503.14620. — [arXiv:2503.14620](https://arxiv.org/abs/2503.14620) [find](https://scholar.google.com/scholar?q=Hikaru+Shimadzu%2C+Takehito+Utsuro%2C+and+Daisuke+Kitayama%2E+2025%2E+Retrieval%2Daugmented+simulacra%3A+Generative+agents+for+up%2Dto%2Ddate+and+knowledge%2Dadaptive+simulations%2E+CoRR%2C+abs%2F2503%2E14620%2E+%E2%80%94+%5BarXiv%3A2503%2E14)
153. Yifan Song, Da Yin, Xiang Yue, Jie Huang, Sujian Li, and Bill Yuchen Lin. 2024. Trial and error: Exploration-based trajectory optimization for LLM agents. CoRR, abs/2403.02502. — [arXiv:2403.02502](https://arxiv.org/abs/2403.02502) [find](https://scholar.google.com/scholar?q=Yifan+Song%2C+Da+Yin%2C+Xiang+Yue%2C+Jie+Huang%2C+Sujian+Li%2C+and+Bill+Yuchen+Lin%2E+2024%2E+Trial+and+error%3A+Exploration%2Dbased+trajectory+optimization+for+LLM+agents%2E+CoRR%2C+abs%2F2403%2E02502%2E+%E2%80%94+%5BarXiv%3A2403%2E02502%5D%28ht)
154. Heydar Soudani, Roxana Petcu, Evangelos Kanoulas, and Faegheh Hasibi. 2024. A survey on recent advances in conversational data generation. [find](https://scholar.google.com/scholar?q=Heydar+Soudani%2C+Roxana+Petcu%2C+Evangelos+Kanoulas%2C+and+Faegheh+Hasibi%2E+2024%2E+A+survey+on+recent+advances+in+conversational+data+generation%2E)
155. Marc Steen, Lottie Kuijt-Evers, and Jente Klok. 2007. Early user involvement in research and design projects – a review of methods and practices. In 23rd EGOS Colloquium, volume 5, pages 1–21. [find](https://scholar.google.com/scholar?q=Marc+Steen%2C+Lottie+Kuijt%2DEvers%2C+and+Jente+Klok%2E+2007%2E+Early+user+involvement+in+research+and+design+projects+%E2%80%93+a+review+of+methods+and+practices%2E+In+23rd+EGOS+Colloquium%2C+volume+5%2C+pages+1%E2%80%9321%2E)
156. Elizabeth Stuart. 2010. Matching methods for causal inference: A review and a look forward. Statistical Science: A Review Journal of the Institute of Mathematical Statistics, 25(1):1–21. [find](https://scholar.google.com/scholar?q=Elizabeth+Stuart%2E+2010%2E+Matching+methods+for+causal+inference%3A+A+review+and+a+look+forward%2E+Statistical+Science%3A+A+Review+Journal+of+the+Institute+of+Mathematical+Statistics%2C+25%281%29%3A1%E2%80%9321%2E)
157. Yihong Tang, Bo Wang, Xu Wang, Dongming Zhao, Jing Liu, Ruifang He, and Yuexian Hou. 2025. Role-break: Character hallucination as a jailbreak attack in role-playing systems. In Proceedings of the 31st International Conference on Computational Linguistics, COLING 2025, pages 7386–7402. Association fo… [find](https://scholar.google.com/scholar?q=Yihong+Tang%2C+Bo+Wang%2C+Xu+Wang%2C+Dongming+Zhao%2C+Jing+Liu%2C+Ruifang+He%2C+and+Yuexian+Hou%2E+2025%2E+Role%2Dbreak%3A+Character+hallucination+as+a+jailbreak+attack+in+role%2Dplaying+systems%2E+In+Proceedings+of+the+31st)
158. Meiling Tao, Xuechen Liang, Tianyu Shi, Lei Yu, and Yiting Xie. 2024. Rolecraft-glm: Advancing personalized role-playing in large language models. CoRR, abs/2401.09432. [find](https://scholar.google.com/scholar?q=Meiling+Tao%2C+Xuechen+Liang%2C+Tianyu+Shi%2C+Lei+Yu%2C+and+Yiting+Xie%2E+2024%2E+Rolecraft%2Dglm%3A+Advancing+personalized+role%2Dplaying+in+large+language+models%2E+CoRR%2C+abs%2F2401%2E09432%2E)
159. Silvia Terragni, Modestas Filipavicius, Nghia Khau, Bruna Guedes, André Ferreira Manso, and Roland Mathis. 2023. In-context learning user simulators for task-oriented dialog systems. CoRR, abs/2306.00774. — [arXiv:2306.00774](https://arxiv.org/abs/2306.00774) [find](https://scholar.google.com/scholar?q=Silvia+Terragni%2C+Modestas+Filipavicius%2C+Nghia+Khau%2C+Bruna+Guedes%2C+Andr%C3%A9+Ferreira+Manso%2C+and+Roland+Mathis%2E+2023%2E+In%2Dcontext+learning+user+simulators+for+task%2Doriented+dialog+systems%2E+CoRR%2C+abs%2F2306%2E00)
160. Gerald Tesauro. 1994. Td-gammon, a self-teaching backgammon program, achieves master-level play. Neural Computation, 6(2):215–219. [find](https://scholar.google.com/scholar?q=Gerald+Tesauro%2E+1994%2E+Td%2Dgammon%2C+a+self%2Dteaching+backgammon+program%2C+achieves+master%2Dlevel+play%2E+Neural+Computation%2C+6%282%29%3A215%E2%80%93219%2E)
161. Emanuel Todorov, Tom Erez, and Yuval Tassa. 2012. Mujoco: A physics engine for model-based control. In 2012 IEEE/RSJ International Conference on Intelligent Robots and Systems, IROS 2012, pages 5026– 5033. IEEE. [find](https://scholar.google.com/scholar?q=Emanuel+Todorov%2C+Tom+Erez%2C+and+Yuval+Tassa%2E+2012%2E+Mujoco%3A+A+physics+engine+for+model%2Dbased+control%2E+In+2012+IEEE%2FRSJ+International+Conference+on+Intelligent+Robots+and+Systems%2C+IROS+2012%2C+pages+5026%E2%80%93+)
162. Michael Tomasello. 2010. Origins of Human Communication. MIT Press. [find](https://scholar.google.com/scholar?q=Michael+Tomasello%2E+2010%2E+Origins+of+Human+Communication%2E+MIT+Press%2E)
163. Hugo Touvron, Thibaut Lavril, Gautier Izacard, Xavier Martinet, Marie-Anne Lachaux, Timothée Lacroix, Baptiste Rozière, Naman Goyal, Eric Hambro, Faisal Azhar, Aurélien Rodriguez, Armand Joulin, Edouard Grave, and Guillaume Lample. 2023. [Llama: Open and efficient foundation language models](https://md.research.elamur.ai/free/en/papers/touvron-2023-llama-open-efficient-foundation-language/). CoRR, ab…
164. Kenneth Train. 2009. Discrete Choice Methods with Simulation. Cambridge University Press, New York, NY. [find](https://scholar.google.com/scholar?q=Kenneth+Train%2E+2009%2E+Discrete+Choice+Methods+with+Simulation%2E+Cambridge+University+Press%2C+New+York%2C+NY%2E)
165. Quan Tu, Shilong Fan, Zihang Tian, Tianhao Shen, Shuo Shang, Xin Gao, and Rui Yan. 2024. [Charactereval: A chinese benchmark for role-playing conversational agent evaluation](https://md.research.elamur.ai/free/en/papers/tu-2024-charactereval-chinese-benchmark-role-playing/). In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2024,…
166. Salih Tutun, Marina E. Johnson, Abdulaziz Ahmed, Abdullah Albizri, Sedat Irgil, Ilker Yesilkaya, Esma Nur Ucar, Tanalp Sengun, and Antoine Harfouche. 2023. An ai-based decision support system for predicting mental health disorders. Information Systems Frontiers, 25(3):1261–1276. [find](https://scholar.google.com/scholar?q=Salih+Tutun%2C+Marina+E%2E+Johnson%2C+Abdulaziz+Ahmed%2C+Abdullah+Albizri%2C+Sedat+Irgil%2C+Ilker+Yesilkaya%2C+Esma+Nur+Ucar%2C+Tanalp+Sengun%2C+and+Antoine+Harfouche%2E+2023%2E+An+ai%2Dbased+decision+support+system+for+pred)
167. Oriol Vinyals and Quoc V. Le. 2015. [A neural conversational model](https://md.research.elamur.ai/free/en/papers/vinyals-2015-neural-conversational-model/). In Proceedings of the 32nd International Conference on Machine Learning, ICML 2015 Workshop on Deep Learning.
168. Yanming Wan, Jiaxing Wu, Marwa Abdulhai, Lior Shani, and Natasha Jaques. 2025. Enhancing personalized multi-turn dialogue with curiosity reward. CoRR, abs/2504.03206. — [arXiv:2504.03206](https://arxiv.org/abs/2504.03206) [find](https://scholar.google.com/scholar?q=Yanming+Wan%2C+Jiaxing+Wu%2C+Marwa+Abdulhai%2C+Lior+Shani%2C+and+Natasha+Jaques%2E+2025%2E+Enhancing+personalized+multi%2Dturn+dialogue+with+curiosity+reward%2E+CoRR%2C+abs%2F2504%2E03206%2E+%E2%80%94+%5BarXiv%3A2504%2E03206%5D%28https%3A%2F%2Farxi)
169. Lei Wang, Jingsen Zhang, Hao Yang, Zhiyuan Chen, Jiakai Tang, Zeyu Zhang, Xu Chen, Yankai Lin, Hao Sun, Ruihua Song, Xin Zhao, Jun Xu, Zhicheng Dou, Jun Wang, and Ji-Rong Wen. 2025a. User behavior simulation with large language model-based agents. ACM Transactions on Information Systems, 43(2):55:1–… [find](https://scholar.google.com/scholar?q=Lei+Wang%2C+Jingsen+Zhang%2C+Hao+Yang%2C+Zhiyuan+Chen%2C+Jiakai+Tang%2C+Zeyu+Zhang%2C+Xu+Chen%2C+Yankai+Lin%2C+Hao+Sun%2C+Ruihua+Song%2C+Xin+Zhao%2C+Jun+Xu%2C+Zhicheng+Dou%2C+Jun+Wang%2C+and+Ji%2DRong+Wen%2E+2025a%2E+User+behavior+sim)
170. Lei Wang, Jingsen Zhang, Hao Yang, Zhiyuan Chen, Jiakai Tang, Zeyu Zhang, Xu Chen, Yankai Lin, Hao Sun, Ruihua Song, Xin Zhao, Jun Xu, Zhicheng Dou, Jun Wang, and Ji-Rong Wen. 2025b. User behavior simulation with large language model-based agents. ACM Transactions on Information Systems, 43(2):55:1–… [find](https://scholar.google.com/scholar?q=Lei+Wang%2C+Jingsen+Zhang%2C+Hao+Yang%2C+Zhiyuan+Chen%2C+Jiakai+Tang%2C+Zeyu+Zhang%2C+Xu+Chen%2C+Yankai+Lin%2C+Hao+Sun%2C+Ruihua+Song%2C+Xin+Zhao%2C+Jun+Xu%2C+Zhicheng+Dou%2C+Jun+Wang%2C+and+Ji%2DRong+Wen%2E+2025b%2E+User+behavior+sim)
171. Noah Wang, Zhongyuan Peng, Haoran Que, Jiaheng Liu, Wangchunshu Zhou, Yuhan Wu, Hongcheng Guo, Ruitong Gan, Zehao Ni, Jian Yang, Man Zhang, Zhaoxiang Zhang, Wanli Ouyang, Ke Xu, Wenhao Huang, Jie Fu, and Junran Peng. 2024a. [Rolellm: Benchmarking, eliciting, and enhancing role-playing abilities of la…](https://md.research.elamur.ai/free/en/papers/wang-2023-rolellm-benchmarking-eliciting-enhancing-role/)
172. Shen Wang, Tianlong Xu, Hang Li, Chaoli Zhang, Joleen Liang, Jiliang Tang, Philip S. Yu, and Qingsong Wen. 2024b. Large language models for education: A survey and outlook. CoRR, abs/2403.18105. [find](https://scholar.google.com/scholar?q=Shen+Wang%2C+Tianlong+Xu%2C+Hang+Li%2C+Chaoli+Zhang%2C+Joleen+Liang%2C+Jiliang+Tang%2C+Philip+S%2E+Yu%2C+and+Qingsong+Wen%2E+2024b%2E+Large+language+models+for+education%3A+A+survey+and+outlook%2E+CoRR%2C+abs%2F2403%2E18105%2E)
173. Xi Wang, Procheta Sen, Ruizhe Li, and Emine Yilmaz. 2025c. Adaptive retrieval-augmented generation for conversational systems. In Findings of the Association for Computational Linguistics: NAACL 2025, pages 491–503. Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Xi+Wang%2C+Procheta+Sen%2C+Ruizhe+Li%2C+and+Emine+Yilmaz%2E+2025c%2E+Adaptive+retrieval%2Daugmented+generation+for+conversational+systems%2E+In+Findings+of+the+Association+for+Computational+Linguistics%3A+NAACL+2025%2C)
174. Xiaoyu Wang, Ningyuan Xi, Teng Chen, Qingqing Gu, Yue Zhao, Xiaokai Chen, Zhonglin Jiang, Yong Chen, and Luo Ji. 2024c. Multi-party supervised fine-tuning of language models for multi-party dialogue generation. CoRR, abs/2412.05342. — [arXiv:2412.05342](https://arxiv.org/abs/2412.05342) [find](https://scholar.google.com/scholar?q=Xiaoyu+Wang%2C+Ningyuan+Xi%2C+Teng+Chen%2C+Qingqing+Gu%2C+Yue+Zhao%2C+Xiaokai+Chen%2C+Zhonglin+Jiang%2C+Yong+Chen%2C+and+Luo+Ji%2E+2024c%2E+Multi%2Dparty+supervised+fine%2Dtuning+of+language+models+for+multi%2Dparty+dialogue+g)
175. Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A. Smith, Daniel Khashabi, and Hannaneh Hajishirzi. 2023. Self-instruct: Aligning language models with self-generated instructions. In Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long… [find](https://scholar.google.com/scholar?q=Yizhong+Wang%2C+Yeganeh+Kordi%2C+Swaroop+Mishra%2C+Alisa+Liu%2C+Noah+A%2E+Smith%2C+Daniel+Khashabi%2C+and+Hannaneh+Hajishirzi%2E+2023%2E+Self%2Dinstruct%3A+Aligning+language+models+with+self%2Dgenerated+instructions%2E+In+Proc)
176. Zifeng Wang, Chun-Liang Li, Vincent Perot, Long T. Le, Jin Miao, Zizhao Zhang, Chen-Yu Lee, and Tomas Pfister. 2024d. Codeclm: Aligning language models with tailored synthetic data. In Findings of the Association for Computational Linguistics: NAACL 2024, pages 3712–3729. Association for Computation… [find](https://scholar.google.com/scholar?q=Zifeng+Wang%2C+Chun%2DLiang+Li%2C+Vincent+Perot%2C+Long+T%2E+Le%2C+Jin+Miao%2C+Zizhao+Zhang%2C+Chen%2DYu+Lee%2C+and+Tomas+Pfister%2E+2024d%2E+Codeclm%3A+Aligning+language+models+with+tailored+synthetic+data%2E+In+Findings+of+the)
177. Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed H. Chi, Quoc V. Le, and Denny Zhou. 2022. [Chain-of-thought prompting elicits reasoning in large language models](https://md.research.elamur.ai/free/en/papers/wei-2022-chain-thought-prompting-elicits-reasoning/). In Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processi…
178. Qingyun Wu, Gagan Bansal, Jieyu Zhang, Yiran Wu, Shaokun Zhang, Erkang Zhu, Beibin Li, Li Jiang, Xiaoyun Zhang, and Chi Wang. 2023. [Autogen: Enabling next-gen LLM applications via multi-agent conversation](https://md.research.elamur.ai/free/en/papers/wu-2023-autogen-enabling-next-gen-llm/) framework. CoRR, abs/2308.08155.
179. Weiqi Wu, Hongqiu Wu, Lai Jiang, Xingyuan Liu, Hai Zhao, and Min Zhang. 2024. From role-play to drama-interaction: An LLM solution. In Findings of the Association for Computational Linguistics, ACL 2024, pages 3271–3290. Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Weiqi+Wu%2C+Hongqiu+Wu%2C+Lai+Jiang%2C+Xingyuan+Liu%2C+Hai+Zhao%2C+and+Min+Zhang%2E+2024%2E+From+role%2Dplay+to+drama%2Dinteraction%3A+An+LLM+solution%2E+In+Findings+of+the+Association+for+Computational+Linguistics%2C+ACL+20)
180. Wei Xiong, Chengshuai Shi, Jiaming Shen, Aviv Rosenberg, Zhen Qin, Daniele Calandriello, Misha Khalman, Rishabh Joshi, Bilal Piot, Mohammad Saleh, Chi Jin, Tong Zhang, and Tianqi Liu. 2025. Building math agents with multi-turn iterative preference learning. In The Thirteenth International Conference… [find](https://scholar.google.com/scholar?q=Wei+Xiong%2C+Chengshuai+Shi%2C+Jiaming+Shen%2C+Aviv+Rosenberg%2C+Zhen+Qin%2C+Daniele+Calandriello%2C+Misha+Khalman%2C+Rishabh+Joshi%2C+Bilal+Piot%2C+Mohammad+Saleh%2C+Chi+Jin%2C+Tong+Zhang%2C+and+Tianqi+Liu%2E+2025%2E+Building+m)
181. Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao, Jiazhan Feng, Chongyang Tao, Qingwei Lin, and Daxin Jiang. 2024a. [Wizardlm: Empowering large pre-trained language models to follow complex instructions](https://md.research.elamur.ai/free/en/papers/xu-2023-wizardlm-empowering-large-pre-trained/). In The Twelfth International Conference on Learning Representations, ICLR 2024.
182. Canwen Xu, Daya Guo, Nan Duan, and Julian J. McAuley. 2023. [Baize: An open-source chat model with parameter-efficient tuning on self-chat data](https://md.research.elamur.ai/free/en/papers/xu-2023-baize-open-source-chat-model/). In Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, EMNLP 2023, pages 6268–6278. Association for Computational Lingui…
183. Hanyi Xu, Wensheng Gan, Zhenlian Qi, Jiayang Wu, and Philip S. Yu. 2024b. Large language models for education: A survey. CoRR, abs/2405.13001. — [arXiv:2405.13001](https://arxiv.org/abs/2405.13001) [find](https://scholar.google.com/scholar?q=Hanyi+Xu%2C+Wensheng+Gan%2C+Zhenlian+Qi%2C+Jiayang+Wu%2C+and+Philip+S%2E+Yu%2E+2024b%2E+Large+language+models+for+education%3A+A+survey%2E+CoRR%2C+abs%2F2405%2E13001%2E+%E2%80%94+%5BarXiv%3A2405%2E13001%5D%28https%3A%2F%2Farxiv%2Eorg%2Fabs%2F2405%2E13001%29)
184. Jing Xu, Arthur Szlam, and Jason Weston. 2022. Beyond goldfish memory: Long-term open-domain conversation. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), ACL 2022, pages 5180–5197. Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Jing+Xu%2C+Arthur+Szlam%2C+and+Jason+Weston%2E+2022%2E+Beyond+goldfish+memory%3A+Long%2Dterm+open%2Ddomain+conversation%2E+In+Proceedings+of+the+60th+Annual+Meeting+of+the+Association+for+Computational+Linguistics+%28V)
185. Rui Xu, Xintao Wang, Jiangjie Chen, Siyu Yuan, Xinfeng Yuan, Jiaqing Liang, Zulong Chen, Xiaoqing Dong, and Yanghua Xiao. 2024c. Character is destiny: Can large language models simulate persona-driven decisions in role-playing? CoRR, abs/2404.12138. — [arXiv:2404.12138](https://arxiv.org/abs/2404.12138) [find](https://scholar.google.com/scholar?q=Rui+Xu%2C+Xintao+Wang%2C+Jiangjie+Chen%2C+Siyu+Yuan%2C+Xinfeng+Yuan%2C+Jiaqing+Liang%2C+Zulong+Chen%2C+Xiaoqing+Dong%2C+and+Yanghua+Xiao%2E+2024c%2E+Character+is+destiny%3A+Can+large+language+models+simulate+persona%2Ddriven)
186. Sanae Yamashita, Koji Inoue, Ao Guo, Shota Mochizuki, Tatsuya Kawahara, and Ryuichiro Higashinaka. 2023. Realpersonachat: A realistic persona chat corpus with interlocutors’ own personalities. In Proceedings of the 37th Pacific Asia Conference on Language, Information and Computation, PACLIC 2023, p… [find](https://scholar.google.com/scholar?q=Sanae+Yamashita%2C+Koji+Inoue%2C+Ao+Guo%2C+Shota+Mochizuki%2C+Tatsuya+Kawahara%2C+and+Ryuichiro+Higashinaka%2E+2023%2E+Realpersonachat%3A+A+realistic+persona+chat+corpus+with+interlocutors%E2%80%99+own+personalities%2E+In+Proc)
187. Tao Yang, Yuhua Zhu, Xiaojun Quan, Cong Liu, and Qifan Wang. 2025. Psyplay: Personality-infused role-playing conversational agents. CoRR, abs/2502.03821. — [arXiv:2502.03821](https://arxiv.org/abs/2502.03821) [find](https://scholar.google.com/scholar?q=Tao+Yang%2C+Yuhua+Zhu%2C+Xiaojun+Quan%2C+Cong+Liu%2C+and+Qifan+Wang%2E+2025%2E+Psyplay%3A+Personality%2Dinfused+role%2Dplaying+conversational+agents%2E+CoRR%2C+abs%2F2502%2E03821%2E+%E2%80%94+%5BarXiv%3A2502%2E03821%5D%28https%3A%2F%2Farxiv%2Eorg%2Fabs%2F250)
188. Fanghua Ye, Jarana Manotumruksa, and Emine Yilmaz. 2022. [Multiwoz 2.4: A multi-domain task-oriented dialogue dataset with essential annotation corrections to improve state tracking evaluation](https://md.research.elamur.ai/free/en/papers/ye-2022-multiwoz-2-4-multi-domain/). In Proceedings of the 23rd Annual Meeting of the Special Interest Group on Discourse and Dialogue, SIGDIAL…
189. Jingheng Ye, Shen Wang, Deqing Zou, Yibo Yan, Kun Wang, Hai-Tao Zheng, Zenglin Xu, Irwin King, Philip S. Yu, and Qingsong Wen. 2025. Position: Llms can be good tutors in foreign language education. CoRR, abs/2502.05467. — [arXiv:2502.05467](https://arxiv.org/abs/2502.05467) [find](https://scholar.google.com/scholar?q=Jingheng+Ye%2C+Shen+Wang%2C+Deqing+Zou%2C+Yibo+Yan%2C+Kun+Wang%2C+Hai%2DTao+Zheng%2C+Zenglin+Xu%2C+Irwin+King%2C+Philip+S%2E+Yu%2C+and+Qingsong+Wen%2E+2025%2E+Position%3A+Llms+can+be+good+tutors+in+foreign+language+education%2E+Co)
190. Se-eun Yoon, Zhankui He, Jessica Maria Echterhoff, and Julian J. McAuley. 2024. Evaluating large language models as generative user simulators for conversational recommendation. In Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Huma… [find](https://scholar.google.com/scholar?q=Se%2Deun+Yoon%2C+Zhankui+He%2C+Jessica+Maria+Echterhoff%2C+and+Julian+J%2E+McAuley%2E+2024%2E+Evaluating+large+language+models+as+generative+user+simulators+for+conversational+recommendation%2E+In+Proceedings+of+the+)
191. Xinfeng Yuan, Siyu Yuan, Yuhan Cui, Tianhe Lin, Xintao Wang, Rui Xu, Jiangjie Chen, and Deqing Yang. 2024. Evaluating character understanding of large language models via character profiling from fictional works. In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processi… [find](https://scholar.google.com/scholar?q=Xinfeng+Yuan%2C+Siyu+Yuan%2C+Yuhan+Cui%2C+Tianhe+Lin%2C+Xintao+Wang%2C+Rui+Xu%2C+Jiangjie+Chen%2C+and+Deqing+Yang%2E+2024%2E+Evaluating+character+understanding+of+large+language+models+via+character+profiling+from+fict)
192. Murong Yue, Wijdane Mifdal, Yixuan Zhang, Jennifer Suh, and Ziyu Yao. 2024. Mathvc: An llm-simulated multi-character virtual classroom for mathematics education. CoRR, abs/2404.06711. — [arXiv:2404.06711](https://arxiv.org/abs/2404.06711) [find](https://scholar.google.com/scholar?q=Murong+Yue%2C+Wijdane+Mifdal%2C+Yixuan+Zhang%2C+Jennifer+Suh%2C+and+Ziyu+Yao%2E+2024%2E+Mathvc%3A+An+llm%2Dsimulated+multi%2Dcharacter+virtual+classroom+for+mathematics+education%2E+CoRR%2C+abs%2F2404%2E06711%2E+%E2%80%94+%5BarXiv%3A2404%2E06)
193. Weihao Zeng, Can Xu, Yingxiu Zhao, Jian-Guang Lou, and Weizhu Chen. 2024. [Automatic instruction evolving for large language models](https://md.research.elamur.ai/free/en/papers/zeng-2024-automatic-instruction-evolving-large-language/). In Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, EMNLP 2024, pages 6998–7018. Association for Computational Linguistics.
194. An Zhang, Yuxin Chen, Leheng Sheng, Xiang Wang, and Tat-Seng Chua. 2024a. On generative agents in recommendation. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, pages 1807–1817. ACM. [find](https://scholar.google.com/scholar?q=An+Zhang%2C+Yuxin+Chen%2C+Leheng+Sheng%2C+Xiang+Wang%2C+and+Tat%2DSeng+Chua%2E+2024a%2E+On+generative+agents+in+recommendation%2E+In+Proceedings+of+the+47th+International+ACM+SIGIR+Conference+on+Research+and+Developm)
195. Erhan Zhang, Xingzhu Wang, Peiyuan Gong, Yankai Lin, and Jiaxin Mao. 2024b. Usimagent: Large language models for simulating search users. In Proceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2024, pages 2687–2692. ACM. [find](https://scholar.google.com/scholar?q=Erhan+Zhang%2C+Xingzhu+Wang%2C+Peiyuan+Gong%2C+Yankai+Lin%2C+and+Jiaxin+Mao%2E+2024b%2E+Usimagent%3A+Large+language+models+for+simulating+search+users%2E+In+Proceedings+of+the+47th+International+ACM+SIGIR+Conference+)
196. Jianguo Zhang, Kun Qian, Zhiwei Liu, Shelby Heinecke, Rui Meng, Ye Liu, Zhou Yu, Huan Wang, Silvio Savarese, and Caiming Xiong. 2024c. [Dialogstudio: Towards richest and most diverse unified dataset collection for conversational AI](https://md.research.elamur.ai/free/en/papers/zhang-2023-dialogstudio-towards-richest-most-diverse/). In Findings of the Association for Computational Linguistics: EACL 2…
197. Saizheng Zhang, Emily Dinan, Jack Urbanek, Arthur Szlam, Douwe Kiela, and Jason Weston. 2018. [Personalizing dialogue agents: I have a dog, do you have pets too?](https://md.research.elamur.ai/free/en/papers/zhang-2018-personalizing-dialogue-agents-i-have/) In Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics, ACL 2018, pages 2204–2213. Association for Comp…
198. Shuo Zhang and Krisztian Balog. 2020. Evaluating conversational recommender systems via user simulation. In KDD ’20: The 26th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, pages 1512–1520. ACM. [find](https://scholar.google.com/scholar?q=Shuo+Zhang+and+Krisztian+Balog%2E+2020%2E+Evaluating+conversational+recommender+systems+via+user+simulation%2E+In+KDD+%E2%80%9920%3A+The+26th+ACM+SIGKDD+Conference+on+Knowledge+Discovery+and+Data+Mining%2C+pages+1512%E2%80%931)
199. Tianjun Zhang, Shishir G. Patil, Naman Jain, Sheng Shen, Matei Zaharia, Ion Stoica, and Joseph E. Gonzalez. 2024d. [RAFT: adapting language model to domain specific RAG](https://md.research.elamur.ai/free/en/papers/zhang-2024-raft-adapting-language-model-domain/). CoRR, abs/2403.10131.
200. Wenqi Zhang, Zhenglin Cheng, Yuanyu He, Mengna Wang, Yongliang Shen, Zeqi Tan, Guiyang Hou, Mingqian He, Yanna Ma, Weiming Lu, and Yueting Zhuang. 2024e. Multimodal self-instruct: Synthetic abstract image and visual reasoning instruction using language model. In Proceedings of the 2024 Conference on… [find](https://scholar.google.com/scholar?q=Wenqi+Zhang%2C+Zhenglin+Cheng%2C+Yuanyu+He%2C+Mengna+Wang%2C+Yongliang+Shen%2C+Zeqi+Tan%2C+Guiyang+Hou%2C+Mingqian+He%2C+Yanna+Ma%2C+Weiming+Lu%2C+and+Yueting+Zhuang%2E+2024e%2E+Multimodal+self%2Dinstruct%3A+Synthetic+abstract+i)
201. Zhehao Zhang, Ryan A. Rossi, Branislav Kveton, Yijia Shao, Diyi Yang, Hamed Zamani, Franck Dernoncourt, Joe Barrow, Tong Yu, Sungchul Kim, Ruiyi Zhang, Jiuxiang Gu, Tyler Derr, Hongjie Chen, Junda Wu, Xiang Chen, Zichao Wang, Subrata Mitra, Nedim Lipka, Nesreen K. Ahmed, and Yu Wang. 2025a. Personal… [find](https://scholar.google.com/scholar?q=Zhehao+Zhang%2C+Ryan+A%2E+Rossi%2C+Branislav+Kveton%2C+Yijia+Shao%2C+Diyi+Yang%2C+Hamed+Zamani%2C+Franck+Dernoncourt%2C+Joe+Barrow%2C+Tong+Yu%2C+Sungchul+Kim%2C+Ruiyi+Zhang%2C+Jiuxiang+Gu%2C+Tyler+Derr%2C+Hongjie+Chen%2C+Junda+Wu%2C)
202. Zheyuan Zhang, Daniel Zhang-Li, Jifan Yu, Linlu Gong, Jinchang Zhou, Zhanxin Hao, Jianxiao Jiang, Jie Cao, Huiqin Liu, Zhiyuan Liu, Lei Hou, and Juanzi Li. 2025b. [Simulating classroom education with llm-empowered agents](https://md.research.elamur.ai/free/en/papers/zhang-2025-simulating-classroom-education-llm-empowered/). In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of…
203. Zijian Zhang, Shuchang Liu, Ziru Liu, Rui Zhong, Qingpeng Cai, Xiangyu Zhao, Chunxu Zhang, Qidong Liu, and Peng Jiang. 2025c. Llm-powered user simulator for recommender system. In Proceedings of the Thirty-Ninth AAAI Conference on Artificial Intelligence, AAAI 2025, pages 13339–13347. AAAI Press. [find](https://scholar.google.com/scholar?q=Zijian+Zhang%2C+Shuchang+Liu%2C+Ziru+Liu%2C+Rui+Zhong%2C+Qingpeng+Cai%2C+Xiangyu+Zhao%2C+Chunxu+Zhang%2C+Qidong+Liu%2C+and+Peng+Jiang%2E+2025c%2E+Llm%2Dpowered+user+simulator+for+recommender+system%2E+In+Proceedings+of+the+T)
204. Chenyang Zhao, Xueying Jia, Vijay Viswanathan, Tongshuang Wu, and Graham Neubig. 2024a. SELF-GUIDE: better task-specific instruction following via self-synthetic finetuning. CoRR, abs/2407.12874. [find](https://scholar.google.com/scholar?q=Chenyang+Zhao%2C+Xueying+Jia%2C+Vijay+Viswanathan%2C+Tongshuang+Wu%2C+and+Graham+Neubig%2E+2024a%2E+SELF%2DGUIDE%3A+better+task%2Dspecific+instruction+following+via+self%2Dsynthetic+finetuning%2E+CoRR%2C+abs%2F2407%2E12874%2E)
205. Haiquan Zhao, Lingyu Li, Shisong Chen, Shuqi Kong, Jiaan Wang, Kexin Huang, Tianle Gu, Yixu Wang, Jian Wang, Dandan Liang, Zhixu Li, Yan Teng, Yanghua Xiao, and Yingchun Wang. 2024b. Esc-eval: Evaluating emotion support conversations in large language models. In Proceedings of the 2024 Conference on… [find](https://scholar.google.com/scholar?q=Haiquan+Zhao%2C+Lingyu+Li%2C+Shisong+Chen%2C+Shuqi+Kong%2C+Jiaan+Wang%2C+Kexin+Huang%2C+Tianle+Gu%2C+Yixu+Wang%2C+Jian+Wang%2C+Dandan+Liang%2C+Zhixu+Li%2C+Yan+Teng%2C+Yanghua+Xiao%2C+and+Yingchun+Wang%2E+2024b%2E+Esc%2Deval%3A+Evaluat)
206. Tiancheng Zhao and Maxine Eskénazi. 2018. Zero-shot dialog generation with cross-domain latent actions. In Proceedings of the 19th Annual SIGdial Meeting on Discourse and Dialogue, pages 1–10. Association for Computational Linguistics. [find](https://scholar.google.com/scholar?q=Tiancheng+Zhao+and+Maxine+Esk%C3%A9nazi%2E+2018%2E+Zero%2Dshot+dialog+generation+with+cross%2Ddomain+latent+actions%2E+In+Proceedings+of+the+19th+Annual+SIGdial+Meeting+on+Discourse+and+Dialogue%2C+pages+1%E2%80%9310%2E+Associa)
207. Tong Zhao, Bo Ni, Wenhao Yu, Zhichun Guo, Neil Shah, and Meng Jiang. 2021. Action sequence augmentation for early graph-based anomaly detection. In Proceedings of the 30th ACM International Conference on Information & Knowledge Management, CIKM ’21, page 2668–2678, New York, NY, USA. Association for… [find](https://scholar.google.com/scholar?q=Tong+Zhao%2C+Bo+Ni%2C+Wenhao+Yu%2C+Zhichun+Guo%2C+Neil+Shah%2C+and+Meng+Jiang%2E+2021%2E+Action+sequence+augmentation+for+early+graph%2Dbased+anomaly+detection%2E+In+Proceedings+of+the+30th+ACM+International+Conference)
208. Zhuohan Li, Dacheng Li, Eric P. Xing, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica. 2023. [Judging llm-as-a-judge with mt-bench and chatbot arena](https://md.research.elamur.ai/free/en/papers/zheng-2023-judging-llm-judge-mt-bench/).
209. Longwei Zheng, Fei Jiang, Xiaoqing Gu, Yuanyuan Li, Gong Wang, and Haomin Zhang. 2025. Teaching via llm-enhanced simulations: Authenticity and barriers to suspension of disbelief. The Internet and Higher Education, 65:100990. [find](https://scholar.google.com/scholar?q=Longwei+Zheng%2C+Fei+Jiang%2C+Xiaoqing+Gu%2C+Yuanyuan+Li%2C+Gong+Wang%2C+and+Haomin+Zhang%2E+2025%2E+Teaching+via+llm%2Denhanced+simulations%3A+Authenticity+and+barriers+to+suspension+of+disbelief%2E+The+Internet+and+Hig)
210. Yinhe Zheng, Guanyi Chen, Minlie Huang, Song Liu, and Xuan Zhu. 2019. Personalized dialogue generation with diversified traits. CoRR, abs/1901.09672. — [arXiv:1901.09672](https://arxiv.org/abs/1901.09672) [find](https://scholar.google.com/scholar?q=Yinhe+Zheng%2C+Guanyi+Chen%2C+Minlie+Huang%2C+Song+Liu%2C+and+Xuan+Zhu%2E+2019%2E+Personalized+dialogue+generation+with+diversified+traits%2E+CoRR%2C+abs%2F1901%2E09672%2E+%E2%80%94+%5BarXiv%3A1901%2E09672%5D%28https%3A%2F%2Farxiv%2Eorg%2Fabs%2F1901%2E09)
211. Jinfeng Zhou, Yongkang Huang, Bosi Wen, Guanqun Bi, Yuxuan Chen, Pei Ke, Zhuang Chen, Xiyao Xiao, Libiao Peng, Kuntian Tang, Rongsheng Zhang, Le Zhang, Tangjie Lv, Zhipeng Hu, Hongning Wang, and Minlie Huang. 2025. Characterbench: Benchmarking character customization of large language models. In Pro… [find](https://scholar.google.com/scholar?q=Jinfeng+Zhou%2C+Yongkang+Huang%2C+Bosi+Wen%2C+Guanqun+Bi%2C+Yuxuan+Chen%2C+Pei+Ke%2C+Zhuang+Chen%2C+Xiyao+Xiao%2C+Libiao+Peng%2C+Kuntian+Tang%2C+Rongsheng+Zhang%2C+Le+Zhang%2C+Tangjie+Lv%2C+Zhipeng+Hu%2C+Hongning+Wang%2C+and+Minli)
212. Yifei Zhou, Andrea Zanette, Jiayi Pan, Sergey Levine, and Aviral Kumar. 2024. Archer: Training language model agents via hierarchical multi-turn RL. In Proceedings of the 41st International Conference on Machine Learning, ICML 2024. [find](https://scholar.google.com/scholar?q=Yifei+Zhou%2C+Andrea+Zanette%2C+Jiayi+Pan%2C+Sergey+Levine%2C+and+Aviral+Kumar%2E+2024%2E+Archer%3A+Training+language+model+agents+via+hierarchical+multi%2Dturn+RL%2E+In+Proceedings+of+the+41st+International+Conference)
213. Banghua Zhu, Evan Frick, Tianhao Wu, Hanlin Zhu, and Jiantao Jiao. 2024a. Starling-7b: Increasing llm helpfulness & harmlessness with rlaif. In First Conference on Language Modeling. [find](https://scholar.google.com/scholar?q=Banghua+Zhu%2C+Evan+Frick%2C+Tianhao+Wu%2C+Hanlin+Zhu%2C+and+Jiantao+Jiao%2E+2024a%2E+Starling%2D7b%3A+Increasing+llm+helpfulness+%26+harmlessness+with+rlaif%2E+In+First+Conference+on+Language+Modeling%2E)
214. Lixi Zhu, Xiaowen Huang, and Jitao Sang. 2025. A llm-based controllable, scalable, human-involved user simulator framework for conversational recommender systems. In Proceedings of the ACM on Web Conference 2025, WWW 2025, pages 4653–4661. ACM. [find](https://scholar.google.com/scholar?q=Lixi+Zhu%2C+Xiaowen+Huang%2C+and+Jitao+Sang%2E+2025%2E+A+llm%2Dbased+controllable%2C+scalable%2C+human%2Dinvolved+user+simulator+framework+for+conversational+recommender+systems%2E+In+Proceedings+of+the+ACM+on+Web+Conf)
215. Minjun Zhu, Linyi Yang, and Yue Zhang. 2024b. [Personality alignment of large language models](https://md.research.elamur.ai/free/en/papers/zhu-2024-personality-alignment-large-language-models/). CoRR, abs/2408.11779.
216. Qi Zhu, Kaili Huang, Zheng Zhang, Xiaoyan Zhu, and Minlie Huang. 2020. [Crosswoz: A large-scale chinese cross-domain task-oriented dialogue dataset](https://md.research.elamur.ai/free/en/papers/zhu-2020-crosswoz-large-scale-chinese-cross/). Transactions of the Association for Computational Linguistics, 8:281–295.
217. Weixiang Zhao, Yulin Hu, Yang Deng, Jiahe Guo, Xingyu Sui, Xinyang Han, An Zhang, Yanyan Zhao, Bing Qin, Tat-Seng Chua, and Ting Liu. 2025. [Beware of your po! measuring and mitigating ai safety risks in role-play fine-tuning of llms](https://md.research.elamur.ai/free/en/papers/zhao-2025-beware-your-po-measuring-mitigating/).
218. Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, [find](https://scholar.google.com/scholar?q=Lianmin+Zheng%2C+Wei%2DLin+Chiang%2C+Ying+Sheng%2C+Siyuan+Zhuang%2C+Zhanghao+Wu%2C+Yonghao+Zhuang%2C+Zi+Lin%2C)

*Updated 1 November 2026*