---
title: "Who cites Cinoo Lee — 367 papers of our library"
description: "367 papers of the Elamur Research library cite the works of Cinoo Lee, found in their bibliographies · page 1 of 2 · 1–100; the most cited first."
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---
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# Who cites Cinoo Lee

374 citations of their works from 367 papers of our library (of the 149,439 whose bibliographies we read) · 104 with a page here, the most cited first · page 1 of 2 · 1–100 · [← Cinoo Lee](https://md.research.elamur.ai/free/en/authors/cinoo-lee/)

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1. **[Can Large Language Models Transform Computational Social Science?](https://md.research.elamur.ai/free/en/papers/ziems-2023-large-language-models-transform-computational/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Caleb Ziems, William Held, Omar Shaikh, et al.*2023 · 790 citations*
2. **[Having Beer after Prayer? Measuring Cultural Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/naous-2023-having-beer-after-prayer-measuring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tarek Naous, Michael J. Ryan, Alan Ritter, et al.*2023 · 273 citations*
3. [**Towards Measuring the Representation of Subjective Global Opinions in Language Models arXiv:2306.16388**Esin Durmus, Karina Nguyen, Thomas I. Liao, et al.*2023 · 270 citations*](https://md.research.elamur.ai/free/en/papers/durmus-2023-towards-measuring-representation-subjective-global/)
4. **[Marked Personas: Using Natural Language Prompts to Measure Stereotypes in Language Models](https://md.research.elamur.ai/free/en/papers/cheng-2023-marked-personas-natural-language-prompts/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Myra Cheng, Esin Durmus, Dan Jurafsky*2023 · 246 citations*
5. [**Not what you've signed up for: Compromising Real-World LLM-Integrated Applications with Indirect Prompt Injection arXiv:2302.12173**Kai Greshake, Sahar Abdelnabi, Shailesh Mishra, et al.*2023 · 239 citations*](https://md.research.elamur.ai/free/en/papers/greshake-2023-ve-signed-up-compromising-real/)
6. [**AI Alignment: A Comprehensive Survey arXiv:2310.19852**Jiaming Ji, Tianyi Qiu, Boyuan Chen, et al.*2023 · 173 citations*](https://md.research.elamur.ai/free/en/papers/ji-2023-ai-alignment-comprehensive-survey/)
7. [**A Roadmap to Pluralistic Alignment arXiv:2402.05070**Taylor Sorensen, Jared Moore, Jillian Fisher, et al.*2024 · 143 citations*](https://md.research.elamur.ai/free/en/papers/sorensen-2024-roadmap-pluralistic-alignment/)
8. **[Do LLMs Exhibit Human-like Response Biases? A Case Study in Survey Design](https://md.research.elamur.ai/free/en/papers/tjuatja-2024-do-llms-exhibit-human-like/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Lindia Tjuatja, Valerie Chen, Tongshuang Wu, et al.*2024 · 140 citations*
9. **[Political Compass or Spinning Arrow? Towards More Meaningful Evaluations for Values and Opinions in Large Language Models](https://md.research.elamur.ai/free/en/papers/rottger-2024-political-compass-or-spinning-arrow/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Paul Röttger, Valentin Hofmann, Valentina Pyatkin, et al.*2024 · 137 citations*
10. [**Artificial Artificial Artificial Intelligence: Crowd Workers Widely Use Large Language Models for Text Production Tasks arXiv:2306.07899**Veniamin Veselovsky, Manoel Horta Ribeiro, Robert West*2023 · 127 citations*](https://md.research.elamur.ai/free/en/papers/veselovsky-2023-artificial-artificial-artificial-intelligence-crowd/)
11. **[Quantifying the Persona Effect in LLM Simulations](https://md.research.elamur.ai/free/en/papers/hu-2024-quantifying-persona-effect-llm-simulations/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tiancheng Hu, Nigel Collier*2024 · 116 citations*
12. **[Value Kaleidoscope: Engaging AI with Pluralistic Human Values, Rights, and Duties](https://md.research.elamur.ai/free/en/papers/sorensen-2023-value-kaleidoscope-engaging-ai-pluralistic/) [Proceedings of the AAAI Conference on Artificial Intelligence](https://md.research.elamur.ai/free/en/venues/proceedings-of-the-aaai-conference-on-artificial-intelligence/)**Taylor Sorensen, Liwei Jiang, Jena Hwang, et al.*2023 · 116 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. **[Survey of Cultural Awareness in Language Models: Text and Beyond](https://md.research.elamur.ai/free/en/papers/pawar-2025-survey-cultural-awareness-language-models/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Siddhesh Pawar, Junyeong Park, Jiho Jin, et al.*2025 · 106 citations*
15. **[Towards Measuring and Modeling “Culture” in LLMs: A Survey](https://md.research.elamur.ai/free/en/papers/adilazuarda-2024-measuring-modeling-culture-llms-survey/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Muhammad Farid Adilazuarda, Sagnik Mukherjee, Pradhyumna Lavania, et al.*2024 · 102 citations*
16. **[Not All Countries Celebrate Thanksgiving: On the Cultural Dominance in Large Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-not-all-countries-celebrate-thanksgiving/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Wenxuan Wang, Wenxiang Jiao, Jingyuan Huang, et al.*2024 · 96 citations*
17. **[Having Beer after Prayer? Measuring Cultural Bias in Large Language Models](https://md.research.elamur.ai/free/en/papers/naous-2024-having-beer-after-prayer-measuring/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Tarek Naous, Michael J Ryan, Alan Ritter, et al.*2024 · 95 citations*
18. **[CultureBank: An Online Community-Driven Knowledge Base Towards Culturally Aware Language Technologies](https://md.research.elamur.ai/free/en/papers/shi-2024-culturebank-online-community-driven-knowledge/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Weiyan Shi, Ryan Li, Yutong Zhang, et al.*2024 · 93 citations*
19. **[Aligning Language Models to User Opinions](https://md.research.elamur.ai/free/en/papers/hwang-2023-aligning-language-models-user-opinions/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**EunJeong Hwang, Bodhisattwa Majumder, Niket Tandon*2023 · 93 citations*
20. **[“My Answer is C”: First-Token Probabilities Do Not Match Text Answers in Instruction-Tuned Language Models](https://md.research.elamur.ai/free/en/papers/wang-2024-my-answer-is-c-first/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xinpeng Wang, Bolei Ma, Chengzhi Hu, et al.*2024 · 91 citations*
21. **[Culturally Aware and Adapted NLP: A Taxonomy and a Survey of the State of the Art](https://md.research.elamur.ai/free/en/papers/liu-2025-culturally-aware-adapted-nlp-taxonomy/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Chen Cecilia Liu, Iryna Gurevych, Anna Korhonen*2025 · 90 citations*
22. **[Bridging the Gap: A Survey on Integrating (Human) Feedback for Natural Language Generation](https://md.research.elamur.ai/free/en/papers/fernandes-2023-bridging-gap-survey-integrating-human/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Patrick Fernandes, Aman Madaan, Emmy Liu, et al.*2023 · 84 citations*
23. **[Cultural Alignment in Large Language Models: An Explanatory Analysis Based on Hofstede's Cultural Dimensions](https://md.research.elamur.ai/free/en/papers/masoud-2025-cultural-alignment-large-language-models/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Reem I. Masoud, Ziquan Liu, Martin Ferianc, et al.*2025 · 74 citations*
24. **[Sensitivity, Performance, Robustness: Deconstructing the Effect of Sociodemographic Prompting](https://md.research.elamur.ai/free/en/papers/beck-2024-sensitivity-performance-robustness-deconstructing-effect/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Tilman Beck, Hendrik Schuff, Anne Lauscher, et al.*2024 · 69 citations*
25. **[Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration](https://md.research.elamur.ai/free/en/papers/feng-2024-modular-pluralism-pluralistic-alignment-multi/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Shangbin Feng, Taylor Sorensen, Yuhan Liu, et al.*2024 · 68 citations*
26. [**Dialect prejudice predicts AI decisions about people's character, employability, and criminality arXiv:2403.00742**Valentin Hofmann, Pratyusha Ria Kalluri, Dan Jurafsky, et al.*2024 · 57 citations*](https://md.research.elamur.ai/free/en/papers/hofmann-2024-dialect-prejudice-predicts-ai-decisions/)
27. **[Unintended Impacts of LLM Alignment on Global Representation](https://md.research.elamur.ai/free/en/papers/ryan-2024-unintended-impacts-llm-alignment-global/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Michael J Ryan, William Held, Diyi Yang*2024 · 57 citations*
28. **[The Alternative Annotator Test for LLM-as-a-Judge: How to Statistically Justify Replacing Human Annotators with LLMs](https://md.research.elamur.ai/free/en/papers/calderon-2025-alternative-annotator-test-llm-as/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Nitay Calderon, Roi Reichart, Rotem Dror*2025 · 52 citations*
29. [**Explore, Establish, Exploit: Red Teaming Language Models from Scratch arXiv:2306.09442**Stephen Casper, Jason Lin, Joe Kwon, et al.*2023 · 52 citations*](https://md.research.elamur.ai/free/en/papers/casper-2023-explore-establish-exploit-red-teaming/)
30. **[Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges](https://md.research.elamur.ai/free/en/papers/ma-2025-pragmatics-era-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bolei Ma, Yuting Li, Wei Zhou, et al.*2025 · 49 citations*
31. **[The Effectiveness of LLMs as Annotators: A Comparative Overview and Empirical Analysis of Direct Representation](https://md.research.elamur.ai/free/en/papers/pavlovic-2024-effectiveness-llms-annotators-comparative-overview/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Maja Pavlovic, Massimo Poesio*2024 · 49 citations*
32. **[Beyond Prompt Brittleness: Evaluating the Reliability and Consistency of Political Worldviews in LLMs](https://md.research.elamur.ai/free/en/papers/ceron-2024-beyond-prompt-brittleness-evaluating-reliability/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Tanise Ceron, Neele Falk, Ana Barić, et al.*2024 · 46 citations*
33. **[Benchmarking Distributional Alignment of Large Language Models](https://md.research.elamur.ai/free/en/papers/meister-2025-benchmarking-distributional-alignment-large-language/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Nicole Meister, Carlos Guestrin, Tatsunori Hashimoto*2025 · 35 citations*
34. [**SafetyPrompts: a Systematic Review of Open Datasets for Evaluating and Improving Large Language Model Safety arXiv:2404.05399**Paul Rottger, Fabio Pernisi, Bertie Vidgen, et al.*2024 · 33 citations*](https://md.research.elamur.ai/free/en/papers/rottger-2024-safetyprompts-systematic-review-open-datasets/)
35. **[Persona-DB: Efficient Large Language Model Personalization for Response Prediction with Collaborative Data Refinement](https://md.research.elamur.ai/free/en/papers/sun-2025-persona-db-efficient-large-language/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Chenkai Sun, Ke Yang, Revanth Gangi Reddy, et al.*2025 · 29 citations*
36. **[Separating Tongue from Thought: Activation Patching Reveals Language-Agnostic Concept Representations in Transformers](https://md.research.elamur.ai/free/en/papers/dumas-2025-separating-tongue-thought-activation-patching/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Clément Dumas, Chris Wendler, Veniamin Veselovsky, et al.*2025 · 27 citations*
37. **[“Fifty Shades of Bias”: Normative Ratings of Gender Bias in GPT Generated English Text](https://md.research.elamur.ai/free/en/papers/hada-2023-fifty-shades-bias-normative-ratings/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Rishav Hada, Agrima Seth, Harshita Diddee, et al.*2023 · 27 citations*
38. **[Personalized Generation In Large Model Era: A Survey](https://md.research.elamur.ai/free/en/papers/xu-2025-personalized-generation-large-model-era/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiyan Xu, Jinghao Zhang, Alireza Salemi, et al.*2025 · 24 citations*
39. [**Language Model Alignment in Multilingual Trolley Problems arXiv:2407.02273**Zhijing Jin, Max Kleiman-Weiner, Giorgio Piatti, et al.*2024 · 23 citations*](https://md.research.elamur.ai/free/en/papers/jin-2024-language-model-alignment-multilingual-trolley/)
40. **[Beyond Demographics: Fine-tuning Large Language Models to Predict Individuals' Subjective Text Perceptions](https://md.research.elamur.ai/free/en/papers/orlikowski-2025-beyond-demographics-fine-tuning-large/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Matthias Orlikowski, Jiaxin Pei, Paul Röttger, et al.*2025 · 22 citations*
41. **[Can Language Models Reason about Individualistic Human Values and Preferences?](https://md.research.elamur.ai/free/en/papers/jiang-2025-can-language-models-reason-about/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Liwei Jiang, Taylor Sorensen, Sydney Levine, et al.*2025 · 21 citations*
42. **[Can Unconfident LLM Annotations Be Used for Confident Conclusions?](https://md.research.elamur.ai/free/en/papers/gligoric-2025-can-unconfident-llm-annotations-be/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Kristina Gligorić, Tijana Zrnic, Cinoo Lee, et al.*2025 · 19 citations*
43. **[Conformity in Large Language Models](https://md.research.elamur.ai/free/en/papers/zhu-2025-conformity-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xiaochen Zhu, Caiqi Zhang, Tom Stafford, et al.*2025 · 18 citations*
44. **[IssueBench: Millions of Realistic Prompts for Measuring Issue Bias in LLM Writing Assistance](https://md.research.elamur.ai/free/en/papers/rottger-2026-issuebench-millions-realistic-prompts-measuring/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Paul Röttger, Musashi Hinck, Valentin Hofmann, et al.*2026 · 16 citations*
45. **[Bridging Cultural Nuances in Dialogue Agents through Cultural Value Surveys](https://md.research.elamur.ai/free/en/papers/cao-2024-bridging-cultural-nuances-dialogue-agents/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Yong Cao, Min Chen, Daniel Hershcovich*2024 · 16 citations*
46. **[Value Profiles for Encoding Human Variation](https://md.research.elamur.ai/free/en/papers/sorensen-2025-value-profiles-encoding-human-variation/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Taylor Sorensen, Pushkar Mishra, Roma Patel, et al.*2025 · 15 citations*
47. **[When One LLM Drools, Multi-LLM Collaboration Rules](https://md.research.elamur.ai/free/en/papers/feng-2026-when-one-llm-drools-multi/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Shangbin Feng, Wenxuan Ding, Alisa Liu, et al.*2026 · 14 citations*
48. [**Psychometric Alignment: Capturing Human Knowledge Distributions via Language Models arXiv:2407.15645**Joy He-Yueya, Wanjing Anya Ma, Kanishk Gandhi, et al.*2024 · 12 citations*](https://md.research.elamur.ai/free/en/papers/he-yueya-2024-psychometric-alignment-capturing-human-knowledge/)
49. [**Aligning Large Language Models with Human Opinions through Persona Selection and Value — Belief — Norm Reasoning arXiv:2311.08385**Do Xuan Long, Kenji Kawaguchi, Min-Yen Kan, et al.*2023 · 12 citations*](https://md.research.elamur.ai/free/en/papers/long-2023-aligning-large-language-models-human/)
50. **[Algorithmic Fidelity of Large Language Models in Generating Synthetic German Public Opinions: A Case Study](https://md.research.elamur.ai/free/en/papers/ma-2025-algorithmic-fidelity-large-language-models/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bolei Ma, Berk Yoztyurk, Anna-Carolina Haensch, et al.*2025 · 10 citations*
51. **[A Rose by Any Other Name: LLM-Generated Explanations Are Good Proxies for Human Explanations to Collect Label Distributions on NLI](https://md.research.elamur.ai/free/en/papers/chen-2025-rose-any-other-name-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Beiduo Chen, Siyao Peng, Anna Korhonen, et al.*2025 · 9 citations*
52. **[Thinking beyond the anthropomorphic paradigm benefits LLM research](https://md.research.elamur.ai/free/en/papers/ibrahim-2026-thinking-beyond-anthropomorphic-paradigm-benefits/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lujain Ibrahim, Myra Cheng*2026 · 8 citations*
53. **[Lost in Simulation: LLM-Simulated Users are Unreliable Proxies for Human Users in Agentic Evaluations](https://md.research.elamur.ai/free/en/papers/seshadri-2026-lost-simulation-llm-simulated-users/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Preethi Seshadri, Samuel Cahyawijaya, Ayomide Odumakinde, et al.*2026 · 5 citations*
54. **[Anthropomimetic Uncertainty: What Verbalized Uncertainty in Language Models is Missing](https://md.research.elamur.ai/free/en/papers/ulmer-2026-anthropomimetic-uncertainty-what-verbalized-uncertainty/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Dennis Ulmer, Alexandra Lorson, Ivan Titov, et al.*2026 · 4 citations*
55. **[Do Political Opinions Transfer Between Western Languages? An Analysis of Unaligned and Aligned Multilingual LLMs](https://md.research.elamur.ai/free/en/papers/weeber-2026-do-political-opinions-transfer-between/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Franziska Weeber, Tanise Ceron, Sebastian Padó*2026 · 4 citations*
56. **[Democratic or Authoritarian? Probing a New Dimension of Political Biases in Large Language Models](https://md.research.elamur.ai/free/en/papers/piedrahita-2026-democratic-or-authoritarian-probing-new/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**David Guzman Piedrahita, Irene Strauss, Rada Mihalcea, et al.*2026 · 3 citations*
57. **[Do Large Language Models Reflect Demographic Pluralism in Safety?](https://md.research.elamur.ai/free/en/papers/naseem-2026-do-large-language-models-reflect/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Usman Naseem, Gautam Siddharth Kashyap, Sushant Kumar Ray, et al.*2026 · 3 citations*
58. **[Comparing Moral Values in Western English-speaking societies and LLMs with Word Associations](https://md.research.elamur.ai/free/en/papers/xiang-2025-comparing-moral-values-western-english/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Chaoyi Xiang, Chunhua Liu, Simon De Deyne, et al.*2025 · 3 citations*
59. **[AutoMonitor-Bench: Evaluating the Reliability of LLM-Based Misbehavior Monitor](https://md.research.elamur.ai/free/en/papers/yang-2026-automonitor-bench-evaluating-reliability-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Shu Yang, Jingyu Hu, Tong Li, et al.*2026 · 2 citations*
60. **[From Fact to Judgment: Investigating the Impact of Task Framing on LLM Conviction in Dialogue Systems](https://md.research.elamur.ai/free/en/papers/rabbani-2026-fact-judgment-investigating-impact-task/) [International Workshop on Spoken Dialogue System Technology](https://md.research.elamur.ai/free/en/venues/iwsds/)**Parisa Rabbani, Nimet Beyza Bozdag, Dilek Hakkani-Tur*2026 · 2 citations*
61. **[The Hidden Bias: A Study on Explicit and Implicit Political Stereotypes in Large Language Models](https://md.research.elamur.ai/free/en/papers/lohr-2026-hidden-bias-study-explicit-implicit/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Konrad Löhr, Shuzhou Yuan, Michael Färber*2026 · 2 citations*
62. **[Among Us: Measuring and Mitigating Malicious Contributions in Model Collaboration Systems](https://md.research.elamur.ai/free/en/papers/yang-2026-among-us-measuring-mitigating-malicious/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ziyuan Yang, Wenxuan Ding, Shangbin Feng, et al.*2026 · 1 citation*
63. **[Attention to Non-Adopters](https://md.research.elamur.ai/free/en/papers/zhou-2026-attention-non-adopters/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Kaitlyn Zhou, Kristina Gligorić, Myra Cheng, et al.*2026 · 1 citation*
64. [**Children's English Reading Story Generation via Supervised Fine-Tuning of Compact LLMs with Controllable Difficulty and Safety**Qian Shen, Fanghua Cao, Min Yao, et al.*2026 · 1 citation*](https://md.research.elamur.ai/free/en/papers/shen-2026-children-s-english-reading-story/)
65. **[CuMA: Aligning LLMs with Sparse Cultural Values via Demographic-Aware Mixture of Adapters](https://md.research.elamur.ai/free/en/papers/sun-2026-cuma-aligning-llms-sparse-cultural/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ao Sun, Xiaoyu Wang, Zhe Tan, et al.*2026 · 1 citation*
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75. **[Can Persona-Prompted LLMs Emulate Subgroup Values? An Empirical Analysis of Generalisability and Fairness in Cultural Alignment](https://md.research.elamur.ai/free/en/papers/tan-2026-can-persona-prompted-llms-emulate/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Bryan Chen Zhengyu Tan, Zhengyuan Liu, Xiaoyuan Yi, et al.*2026*
76. **[Carefully Considering Culture: Analyzing LLM Alignment in Single- and Multi-Cultural Settings using Cultural Consensus Theory](https://md.research.elamur.ai/free/en/papers/pothugunta-2026-carefully-considering-culture-analyzing-llm/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Krishna Pothugunta, John P. Lalor*2026*
77. **[Confident, Calibrated, or Complicit: Safety Alignment and Ideological Bias in LLM Hate Speech Detection](https://md.research.elamur.ai/free/en/papers/selvaganapathy-2026-confident-calibrated-or-complicit-safety/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Sanjeevan Selvaganapathy, Mehwish Nasim*2026*
78. **[Convergent Demographic Utility Hierarchies: Geometry of Intersectional Values in LLMs](https://md.research.elamur.ai/free/en/papers/sainath-2026-convergent-demographic-utility-hierarchies-geometry/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Pravish Sainath*2026*
79. **[DialDefer: A Framework for Detecting and Mitigating LLM Dialogic Deference](https://md.research.elamur.ai/free/en/papers/rabbani-2026-dialdefer-framework-detecting-mitigating-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Parisa Rabbani, Priyam Sahoo, Ruben Mathew, et al.*2026*
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94. **[Social Welfare Function Leaderboard: On the Emergence of LLM Agents as the Welfare Dictator](https://md.research.elamur.ai/free/en/papers/shi-2026-social-welfare-function-leaderboard-emergence/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Zhengliang Shi, Ruotian Ma, Jen-tse Huang, et al.*2026*
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96. **[The American Palimpsest: Quantifying South Asian English Dialect Erasure in LLMs](https://md.research.elamur.ai/free/en/papers/bharati-2026-american-palimpsest-quantifying-south-asian/) [Workshop on Cross-Cultural Considerations in NLP](https://md.research.elamur.ai/free/en/venues/c3nlp/)**Soumedhik Bharati, Shibam Mandal, Swarup Kr Ghosh, et al.*2026*
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100. **[User-Assistant Bias in LLMs](https://md.research.elamur.ai/free/en/papers/pan-2026-user-assistant-bias-llms/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Xu Pan, Jingxuan Fan, Zidi Xiong, et al.*2026*

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