---
title: "Who cites Xiangnan He — 292 papers of our library"
description: "292 papers of the Elamur Research library cite the works of Xiangnan He, found in their bibliographies; the most cited first."
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---
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# Who cites Xiangnan He

300 citations of their works from 292 papers of our library (of the 149,439 whose bibliographies we read) · 40 with a page here, the most cited first · [← Xiangnan He](https://md.research.elamur.ai/free/en/authors/xiangnan-he/)

1. **[A Survey of Large Language Models](https://md.research.elamur.ai/free/en/papers/zhao-2023-survey-large-language-models/) [Frontiers of Computer Science](https://md.research.elamur.ai/free/en/venues/frontiers-of-computer-science/)**Wayne Xin Zhao, Kun Zhou, Junyi Li, et al.*2023 · 2,875 citations*
2. **[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/) [International Conference on Learning Representations (ICLR)](https://md.research.elamur.ai/free/en/venues/international-conference-on-learning-representations-iclr/)**Can Xu, Qingfeng Sun, Kai Zheng, et al.*2023 · 741 citations*
3. **[Transferable Multi-Domain State Generator for Task-Oriented Dialogue Systems](https://md.research.elamur.ai/free/en/papers/wu-2019-transferable-multi-domain-state-generator/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chien-Sheng Wu, Andrea Madotto, Ehsan Hosseini-Asl, et al.*2019 · 628 citations*
4. [**TALLRec: An Effective and Efficient Tuning Framework to Align Large Language Model with Recommendation arXiv:2305.00447**Keqin Bao; Jizhi Zhang; Yang Zhang; Wenjie Wang; Fuli Feng;, Xiangnan He*2023 · 531 citations*](https://md.research.elamur.ai/free/en/papers/bao-2023-tallrec-effective-efficient-tuning-framework/)
5. [**A Simple Language Model for Task-Oriented Dialogue arXiv:2005.00796**Ehsan Hosseini-Asl, Bryan McCann, Chien-Sheng Wu, et al.*2020 · 399 citations*](https://md.research.elamur.ai/free/en/papers/hosseini-asl-2020-simple-language-model-task-oriented/)
6. **[TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance](https://md.research.elamur.ai/free/en/papers/zhu-2021-tat-qa-question-answering-benchmark/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Fengbin Zhu, Wenqiang Lei, Youcheng Huang, et al.*2021 · 397 citations*
7. **[Large Language Models are Zero-Shot Rankers for Recommender Systems](https://md.research.elamur.ai/free/en/papers/hou-2023-large-language-models-zero-shot/) [Lecture notes in computer science](https://md.research.elamur.ai/free/en/venues/lecture-notes-in-computer-science/)**Yupeng Hou, Junjie Zhang, Zihan Lin, et al.*2023 · 394 citations*
8. **[Efficient Dialogue State Tracking by Selectively Overwriting Memory](https://md.research.elamur.ai/free/en/papers/kim-2020-efficient-dialogue-state-tracking-selectively/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sungdong Kim, Sohee Yang, Gyuwan Kim, et al.*2020 · 270 citations*
9. **[MinTL: Minimalist Transfer Learning for Task-Oriented Dialogue Systems](https://md.research.elamur.ai/free/en/papers/lin-2020-mintl-minimalist-transfer-learning-task/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Zhaojiang Lin, Andrea Madotto, Genta Indra Winata, et al.*2020 · 240 citations*
10. **[End-to-End Neural Pipeline for Goal-Oriented Dialogue Systems using GPT-2](https://md.research.elamur.ai/free/en/papers/ham-2020-end-end-neural-pipeline-goal/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Donghoon Ham, Jeong-Gwan Lee, Youngsoo Jang, et al.*2020 · 230 citations*
11. **[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 (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Qi Zhu, Kaili Huang, Zheng Zhang, et al.*2020 · 147 citations*
12. **[In-Context Learning for Few-Shot Dialogue State Tracking](https://md.research.elamur.ai/free/en/papers/hu-2022-context-learning-few-shot-dialogue/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yushi Hu, Chia-Hsuan Lee, Tianbao Xie, et al.*2022 · 144 citations*
13. [**From Persona to Personalization: A Survey on Role-Playing Language Agents arXiv:2404.18231**Jiangjie Chen, Xintao Wang, Rui Xu, et al.*2024 · 115 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-persona-personalization-survey-role-playing/)
14. **[Find or Classify? Dual Strategy for Slot-Value Predictions on Multi-Domain Dialog State Tracking](https://md.research.elamur.ai/free/en/papers/zhang-2020-find-or-classify-dual-strategy/) [Joint Conference on Lexical and Computational Semantics (*SEM)](https://md.research.elamur.ai/free/en/venues/starsem/)**Jianguo Zhang, Kazuma Hashimoto, Chien-Sheng Wu, et al.*2020 · 79 citations*
15. **[Knowledge Graph Retrieval-Augmented Generation for LLM-based Recommendation](https://md.research.elamur.ai/free/en/papers/wang-2025-knowledge-graph-retrieval-augmented-generation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shijie Wang, Wenqi Fan, Yue Feng, et al.*2025 · 77 citations*
16. **[Unveiling Language-Specific Features in Large Language Models via Sparse Autoencoders](https://md.research.elamur.ai/free/en/papers/deng-2025-unveiling-language-specific-features-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Boyi Deng, Yu Wan, Baosong Yang, et al.*2025 · 18 citations*
17. **[Personalized Text Generation with Contrastive Activation Steering](https://md.research.elamur.ai/free/en/papers/zhang-2025-personalized-text-generation-contrastive-activation/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jinghao Zhang, Yuting Liu, Wenjie Wang, et al.*2025 · 13 citations*
18. **[LaMP-QA: A Benchmark for Personalized Long-form Question Answering](https://md.research.elamur.ai/free/en/papers/salemi-2025-lamp-qa-benchmark-personalized-long/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Alireza Salemi, Hamed Zamani*2025 · 12 citations*
19. **[Latent Inter-User Difference Modeling for LLM Personalization](https://md.research.elamur.ai/free/en/papers/qiu-2025-latent-inter-user-difference-modeling/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yilun Qiu, Tianhao Shi, Xiaoyan Zhao, et al.*2025 · 12 citations*
20. **[OneRec-Think: In-Text Reasoning for Generative Recommendation](https://md.research.elamur.ai/free/en/papers/liu-2026-onerec-think-text-reasoning-generative/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhanyu Liu, Shiyao Wang, Xingmei Wang, et al.*2026 · 10 citations*
21. **[Examining False Positives under Inference Scaling for Mathematical Reasoning](https://md.research.elamur.ai/free/en/papers/wang-2025-examining-false-positives-under-inference/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Yu Wang, Nan Yang, Liang Wang, et al.*2025 · 9 citations*
22. [**Are Current Task-oriented Dialogue Systems Able to Satisfy Impolite Users? arXiv:2210.12942**Zhiqiang Hu, Roy Kaa-Wei Lee, Nancy F. Chen*2022 · 4 citations*](https://md.research.elamur.ai/free/en/papers/hu-2022-current-task-oriented-dialogue-systems/)
23. **[Controllable LLM Reasoning via Sparse Autoencoder-Based Steering](https://md.research.elamur.ai/free/en/papers/fang-2026-controllable-llm-reasoning-sparse-autoencoder/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yi Fang, Wenjie Wang, Mingfeng Xue, et al.*2026 · 3 citations*
24. [**Qwen-Scope: Turning Sparse Features into Development Tools for Large Language Models arXiv:2605.11887**Boyi Deng, Xu Wang, Yaoning Wang, et al.*2026 · 3 citations*](https://md.research.elamur.ai/free/en/papers/deng-2026-qwen-scope-turning-sparse/)
25. **[What Makes LLMs Effective Sequential Recommenders? A Study on Preference Intensity and Temporal Context](https://md.research.elamur.ai/free/en/papers/ouyang-2026-what-makes-llms-effective-sequential/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Zhongyu Ouyang, Qianlong Wen, Chunhui Zhang, et al.*2026 · 1 citation*
26. **[Adaptive and Representative Multi-Interest Modeling for Recommendation with Large Language Model](https://md.research.elamur.ai/free/en/papers/wang-2026-adaptive-representative-multi-interest-modeling/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Ziyan Wang, Yingpeng Du, Tianjun Wei, et al.*2026*
27. **[ChildEval:WHEN LARGE LANGUAGE MODELS MEET CHILDREN'S PERSONALITIES](https://md.research.elamur.ai/free/en/papers/luo-2026-childeval-when-large-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yanyan Luo, Xue Han, Chunxu Zhao, et al.*2026*
28. **[ClusterRAG: Cluster-Based Collaborative Filtering for Personalized Retrieval-Augmented Generation](https://md.research.elamur.ai/free/en/papers/nkhata-2026-clusterrag-cluster-based-collaborative-filtering/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Gibson Nkhata, Uttamasha Anjally Oyshi, Quan Mai, et al.*2026*
29. **[From Past To Path: Masked History Learning for Next-Item Prediction in Generative Recommendation](https://md.research.elamur.ai/free/en/papers/wei-2026-past-path-masked-history-learning/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Kaiwen Wei, Kejun he, Xiaomian Kang, et al.*2026*
30. **[GraphLoRA: Structure-Aware Low-Rank Adaptation for Large Language Model Recommendation](https://md.research.elamur.ai/free/en/papers/mu-2026-graphlora-structure-aware-low-rank/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Lin Mu, Guoji Wang, Li Ni, et al.*2026*
31. **[GrocLM: Grocery Category Recommendation in E-Commerce with Large Language Models](https://md.research.elamur.ai/free/en/papers/zhong-2026-groclm-grocery-category-recommendation-e/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yuan Zhong, Chuanwei Ruan, Moein Hasani, et al.*2026*
32. **[Internalizing Multi-Agent Reasoning for Accurate and Efficient LLM-based Recommendation](https://md.research.elamur.ai/free/en/papers/wu-2026-internalizing-multi-agent-reasoning-accurate/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yang Wu, Haoze Wang, Qian Li, et al.*2026*
33. [**JudgeMeNot: Personalizing Large Language Models to Emulate Judicial Reasoning in Hebrew**Itay Razumenko, Arnon Sturm, Nir Grinberg*2026*](https://md.research.elamur.ai/free/en/papers/razumenko-2026-judgemenot-personalizing-large-language-models/)
34. **[Learning to Retrieve User History and Generate User Profiles for Personalized Persuasiveness Prediction](https://md.research.elamur.ai/free/en/papers/park-2026-learning-retrieve-user-history-generate/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Sejun Park, Yoonah Park, Jongwon Lim, et al.*2026*
35. **[Measuring Mechanistic Independence: Can Bias Be Removed Without Erasing Demographics?](https://md.research.elamur.ai/free/en/papers/shan-2026-measuring-mechanistic-independence-can-bias/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Zhengyang Shan, Aaron Mueller*2026*
36. **[Multilingual Language Models Encode Script Over Linguistic Structure](https://md.research.elamur.ai/free/en/papers/verma-2026-multilingual-language-models-encode-script/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Aastha A K Verma, Anwoy Chatterjee, Mehak Gupta, et al.*2026*
37. **[PrePPER: A Preference Pattern-based Profiling Framework for Explainable Recommendation](https://md.research.elamur.ai/free/en/papers/usumi-2026-prepper-preference-pattern-based-profiling/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Taisuke Usumi, Akiko Masaki, Sanae Muramatsu, et al.*2026*
38. **[Preventing Safety Drift in Large Language Models via Coupled Weight and Activation Constraints](https://md.research.elamur.ai/free/en/papers/peng-2026-preventing-safety-drift-large-language/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Songping Peng, Zhiheng Zhang, Daojian Zeng, et al.*2026*
39. **[TRACER: Early Failure Detection for Task-Oriented Dialogue](https://md.research.elamur.ai/free/en/papers/nourbakhsh-2026-tracer-early-failure-detection-task/) [Annual Meeting of the Special Interest Group on Discourse and Dialogue (SIGDIAL)](https://md.research.elamur.ai/free/en/venues/sigdial/)**Erfan Nourbakhsh, Rocky Slavin, Ke Yang, et al.*2026*
40. **[Unleashing the Native Recommendation Potential: LLM-Based Generative Recommendation via Structured Term Identifiers](https://md.research.elamur.ai/free/en/papers/zhang-2026-unleashing-native-recommendation-potential-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhiyang Zhang, Junda She, Kuo Cai, et al.*2026*

252 more citing papers of our library have no page here yet.

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