---
title: "Who cites Vishal Maini — 188 papers of our library"
description: "188 papers of the Elamur Research library cite the works of Vishal Maini, found in their bibliographies; the most cited first."
canonical: "https://research.elamur.ai/free/en/authors/vishal-maini/cited-by/"
---
[Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/authors/vishal-maini/cited-by/)

[home](https://md.research.elamur.ai/free/en/) / [authors](https://md.research.elamur.ai/free/en/authors/) / [Vishal Maini](https://md.research.elamur.ai/free/en/authors/vishal-maini/) / cited by

# Who cites Vishal Maini

191 citations of their works from 188 papers of our library (of the 149,439 whose bibliographies we read) · 69 with a page here, the most cited first · [← Vishal Maini](https://md.research.elamur.ai/free/en/authors/vishal-maini/)

1. [**Language Models are Few-Shot Learners arXiv:2005.14165**Tom B. Brown, Benjamin Mann, Nick Ryder, et al.*2020 · 14,178 citations*](https://md.research.elamur.ai/free/en/papers/brown-2020-language-models-few-shot-learners/)
2. [**Training language models to follow instructions with human feedback arXiv:2203.02155**Long Ouyang, Jeff Wu, Xu Jiang, et al.*2022 · 10,224 citations*](https://md.research.elamur.ai/free/en/papers/ouyang-2022-training-language-models-follow-instructions/)
3. [**On the Opportunities and Risks of Foundation Models arXiv:2108.07258**Rishi Bommasani, Drew A. Hudson, Ehsan Adeli, et al.*2021 · 3,160 citations*](https://md.research.elamur.ai/free/en/papers/bommasani-2021-opportunities-risks-foundation-models/)
4. [**Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj**Aarohi Srivastava, Abhinav Rastogi, Abhishek Rao, et al.*2022 · 1,756 citations*](https://md.research.elamur.ai/free/en/papers/srivastava-2022-imitation-game-quantifying-extrapolating-capabilities/)
5. **[Language (Technology) is Power: A Critical Survey of “Bias” in NLP](https://md.research.elamur.ai/free/en/papers/blodgett-2020-language-technology-is-power-critical/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Su Lin Blodgett, Solon Barocas, Hal Daumé III, et al.*2020 · 1,716 citations*
6. [**LaMDA: Language Models for Dialog Applications arXiv:2201.08239**Romal Thoppilan, Daniel De Freitas, Jamie Hall, et al.*2022 · 1,344 citations*](https://md.research.elamur.ai/free/en/papers/thoppilan-2022-lamda-language-models-dialog-applications/)
7. **[Bias and Fairness in Large Language Models: A Survey](https://md.research.elamur.ai/free/en/papers/gallegos-2023-bias-fairness-large-language-models/) [Computational Linguistics](https://md.research.elamur.ai/free/en/venues/cl/)**Isabel O. Gallegos, Ryan A. Rossi, Joe Barrow, et al.*2023 · 1,082 citations*
8. [**GPQA: A Graduate-Level Google-Proof Q&A Benchmark arXiv:2311.12022**David Rein, Betty Li Hou, Asa Cooper Stickland, et al.*2023 · 1,018 citations*](https://md.research.elamur.ai/free/en/papers/rein-2023-gpqa-graduate-level-google-proof/)
9. [**Universal and Transferable Adversarial Attacks on Aligned Language Models arXiv:2307.15043**Andy Zou, Zifan Wang, Nicholas Carlini, et al.*2023 · 1,005 citations*](https://md.research.elamur.ai/free/en/papers/zou-2023-universal-transferable-adversarial-attacks-aligned/)
10. **[CrowS-Pairs: A Challenge Dataset for Measuring Social Biases in Masked Language Models](https://md.research.elamur.ai/free/en/papers/nangia-2020-crows-pairs-challenge-dataset-measuring/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Nikita Nangia, Clara Vania, Rasika Bhalerao, et al.*2020 · 897 citations*
11. [**WebGPT: Browser-assisted question-answering with human feedback arXiv:2112.09332**Reiichiro Nakano, Jacob Hilton, Suchir Balaji, et al.*2021 · 721 citations*](https://md.research.elamur.ai/free/en/papers/nakano-2021-webgpt-browser-assisted-question-answering/)
12. **[Red Teaming Language Models with Language Models](https://md.research.elamur.ai/free/en/papers/perez-2022-red-teaming-language-models-language/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Ethan Perez, Saffron Huang, Francis Song, et al.*2022 · 700 citations*
13. [**Release Strategies and the Social Impacts of Language Models arXiv:1908.09203**Irene Solaiman, Miles Brundage, Jack Clark, et al.*2019 · 554 citations*](https://md.research.elamur.ai/free/en/papers/solaiman-2019-release-strategies-social-impacts-language/)
14. [**Ethical and social risks of harm from Language Models arXiv:2112.04359**Laura Weidinger, John Mellor, Maribeth Rauh, et al.*2021 · 456 citations*](https://md.research.elamur.ai/free/en/papers/weidinger-2021-ethical-social-risks-harm-language/)
15. [**Tulu 3: Pushing Frontiers in Open Language Model Post-Training arXiv:2411.15124**Nathan Lambert, Jacob Morrison, Valentina Pyatkin, et al.*2024 · 423 citations*](https://md.research.elamur.ai/free/en/papers/lambert-2024-tulu-3-pushing-frontiers-open/)
16. [**Towards Understanding Sycophancy in Language Models arXiv:2310.13548**Mrinank Sharma, Meg Tong, Tomasz Korbak, et al.*2023 · 384 citations*](https://md.research.elamur.ai/free/en/papers/sharma-2023-towards-understanding-sycophancy-language-models/)
17. **[BeaverTails: Towards Improved Safety Alignment of LLM via a Human-Preference Dataset](https://md.research.elamur.ai/free/en/papers/ji-2023-beavertails-towards-improved-safety-alignment/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jiaming Ji, Mickel Liu, Juntao Dai, et al.*2023 · 362 citations*
18. [**Improving alignment of dialogue agents via targeted human judgements arXiv:2209.14375**Amelia Glaese, Nat McAleese, Maja Trębacz, et al.*2022 · 362 citations*](https://md.research.elamur.ai/free/en/papers/glaese-2022-improving-alignment-dialogue-agents-targeted/)
19. [**Scaling Laws for Reward Model Overoptimization arXiv:2210.10760**Leo Gao, John Schulman, Jacob Hilton*2022 · 323 citations*](https://md.research.elamur.ai/free/en/papers/gao-2022-scaling-laws-reward-model-overoptimization/)
20. [**Towards Understanding and Mitigating Social Biases in Language Models arXiv:2106.13219**Paul Pu Liang, Chiyu Wu, Louis-Philippe Morency, et al.*2021 · 271 citations*](https://md.research.elamur.ai/free/en/papers/liang-2021-towards-understanding-mitigating-social-biases/)
21. **[Societal Biases in Language Generation: Progress and Challenges](https://md.research.elamur.ai/free/en/papers/sheng-2021-societal-biases-language-generation-progress/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Emily Sheng, Kai-Wei Chang, Prem Natarajan, et al.*2021 · 257 citations*
22. [**RAFT: Reward rAnked FineTuning for Generative Foundation Model Alignment arXiv:2304.06767**Hanze Dong, Wei Xiong, Deepanshu Goyal, et al.*2023 · 252 citations*](https://md.research.elamur.ai/free/en/papers/dong-2023-raft-reward-ranked-finetuning-generative/)
23. [**Teaching language models to support answers with verified quotes arXiv:2203.11147**Jacob Menick, Maja Trebacz, Vladimir Mikulik, et al.*2022 · 218 citations*](https://md.research.elamur.ai/free/en/papers/menick-2022-teaching-language-models-support-answers/)
24. **[RLHF-V: Towards Trustworthy MLLMs via Behavior Alignment from Fine-grained Correctional Human Feedback](https://md.research.elamur.ai/free/en/papers/yu-2023-rlhf-v-towards-trustworthy-mllms/) [IEEE Computer Society Conference on Computer Vision and Pattern Recognition](https://md.research.elamur.ai/free/en/venues/ieee-computer-society-conference-on-computer-vision-and-pattern-recognition/)**Tianyu Yu, Yuan Yao, Haoye Zhang, et al.*2023 · 217 citations*
25. **[Challenges in Detoxifying Language Models](https://md.research.elamur.ai/free/en/papers/welbl-2021-challenges-detoxifying-language-models/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Johannes Welbl, Amelia Glaese, Jonathan Uesato, et al.*2021 · 213 citations*
26. [**Recursively Summarizing Books with Human Feedback arXiv:2109.10862**Jeff Wu, Long Ouyang, Daniel M. Ziegler, et al.*2021 · 208 citations*](https://md.research.elamur.ai/free/en/papers/wu-2021-recursively-summarizing-books-human-feedback/)
27. [**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/)
28. [**Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision arXiv:2312.09390**Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner, et al.*2023 · 172 citations*](https://md.research.elamur.ai/free/en/papers/burns-2023-weak-strong-generalization-eliciting-strong/)
29. **[Paragraph-level Rationale Extraction through Regularization: A case study on European Court of Human Rights Cases](https://md.research.elamur.ai/free/en/papers/chalkidis-2021-paragraph-level-rationale-extraction-through/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/naacl/)**Ilias Chalkidis, Manos Fergadiotis, Dimitrios Tsarapatsanis, et al.*2021 · 168 citations*
30. **[“I'm sorry to hear that”: Finding New Biases in Language Models with a Holistic Descriptor Dataset](https://md.research.elamur.ai/free/en/papers/smith-2022-i-m-sorry-hear-that/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Eric Michael Smith, Melissa Hall, Melanie Kambadur, et al.*2022 · 167 citations*
31. [**Process Reinforcement through Implicit Rewards arXiv:2502.01456**Ganqu Cui, Lifan Yuan, Zefan Wang, et al.*2025 · 151 citations*](https://md.research.elamur.ai/free/en/papers/cui-2025-process-reinforcement-through-implicit-rewards/)
32. [**Unsolved Problems in ML Safety arXiv:2109.13916**Dan Hendrycks, Nicholas Carlini, John Schulman, et al.*2021 · 151 citations*](https://md.research.elamur.ai/free/en/papers/hendrycks-2021-unsolved-problems-ml-safety/)
33. [**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/)
34. **[Humans or LLMs as the Judge? A Study on Judgement Bias](https://md.research.elamur.ai/free/en/papers/chen-2024-humans-or-llms-as-judge/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Guiming Hardy Chen, Shunian Chen, Ziche Liu, et al.*2024 · 133 citations*
35. **[Quantifying Social Biases in NLP: A Generalization and Empirical Comparison of Extrinsic Fairness Metrics](https://md.research.elamur.ai/free/en/papers/czarnowska-2021-quantifying-social-biases-nlp-generalization/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Paula Czarnowska, Yogarshi Vyas, Kashif Shah*2021 · 133 citations*
36. **[You reap what you sow: On the Challenges of Bias Evaluation Under Multilingual Settings](https://md.research.elamur.ai/free/en/papers/talat-2022-you-reap-what-you-sow/) [BigScience Episode – Workshop on Challenges & Perspectives in Creating Large Language Models](https://md.research.elamur.ai/free/en/venues/bigscience/)**Zeerak Talat, Aurélie Névéol, Stella Biderman, et al.*2022 · 130 citations*
37. [**Large Language Model Alignment: A Survey arXiv:2309.15025**Tianhao Shen, Renren Jin, Yufei Huang, et al.*2023 · 124 citations*](https://md.research.elamur.ai/free/en/papers/shen-2023-large-language-model-alignment-survey/)
38. [**Alignment of Language Agents arXiv:2103.14659**Zachary Kenton, Tom Everitt, Laura Weidinger, et al.*2021 · 120 citations*](https://md.research.elamur.ai/free/en/papers/kenton-2021-alignment-language-agents/)
39. [**Best Practices and Lessons Learned on Synthetic Data arXiv:2404.07503**Ruibo Liu, Jerry Wei, Fangyu Liu, et al.*2024 · 119 citations*](https://md.research.elamur.ai/free/en/papers/liu-2024-best-practices-lessons-learned-synthetic/)
40. [**Measuring Progress on Scalable Oversight for Large Language Models arXiv:2211.03540**Samuel R. Bowman, Jeeyoon Hyun, Ethan Perez, et al.*2022 · 117 citations*](https://md.research.elamur.ai/free/en/papers/bowman-2022-measuring-progress-scalable-oversight-large/)
41. **[On the Intrinsic and Extrinsic Fairness Evaluation Metrics for Contextualized Language Representations](https://md.research.elamur.ai/free/en/papers/cao-2022-intrinsic-extrinsic-fairness-evaluation-metrics/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yang Trista Cao, Yada Pruksachatkun, Kai-Wei Chang, et al.*2022 · 100 citations*
42. [**Safety Alignment Should Be Made More Than Just a Few Tokens Deep arXiv:2406.05946**Xiangyu Qi, Ashwinee Panda, Kaifeng Lyu, et al.*2024 · 97 citations*](https://md.research.elamur.ai/free/en/papers/qi-2024-safety-alignment-should-made-more/)
43. [**Training Socially Aligned Language Models on Simulated Social Interactions arXiv:2305.16960**Ruibo Liu, Ruixin Yang, Chenyan Jia, et al.*2023 · 94 citations*](https://md.research.elamur.ai/free/en/papers/liu-2023-training-socially-aligned-language-models/)
44. **[A Survey of Reinforcement Learning from Human Feedback](https://md.research.elamur.ai/free/en/papers/kaufmann-2023-survey-reinforcement-learning-human-feedback/) [Transactions on Machine Learning Research](https://md.research.elamur.ai/free/en/venues/transactions-on-machine-learning-research/)**Timo Kaufmann, Paul Weng, Viktor Bengs, et al.*2023 · 92 citations*
45. [**Foundational Challenges in Assuring Alignment and Safety of Large Language Models arXiv:2404.09932**Usman Anwar, Abulhair Saparov, Javier Rando, et al.*2024 · 87 citations*](https://md.research.elamur.ai/free/en/papers/anwar-2024-foundational-challenges-assuring-alignment-safety/)
46. **[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*
47. [**Humans or LLMs as the Judge? A Study on Judgement Biases arXiv:2402.10669**Guiming Hardy Chen, Shunian Chen, Ziche Liu, et al.*2024 · 78 citations*](https://md.research.elamur.ai/free/en/papers/chen-2024-humans-llms-judge-study-judgement/)
48. [**Secrets of RLHF in Large Language Models Part II: Reward Modeling arXiv:2401.06080**Binghai Wang, Rui Zheng, Lu Chen, et al.*2024 · 72 citations*](https://md.research.elamur.ai/free/en/papers/wang-2024-secrets-rlhf-large-language-models/)
49. **[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*
50. **[MLLM-Protector: Ensuring MLLM's Safety without Hurting Performance](https://md.research.elamur.ai/free/en/papers/pi-2024-mllm-protector-ensuring-mllm-s/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Renjie Pi, Tianyang Han, Jianshu Zhang, et al.*2024 · 58 citations*
51. [**Personalisation within bounds: A risk taxonomy and policy framework for the alignment of large language models with personalised feedback arXiv:2303.05453**Hannah Rose Kirk, Bertie Vidgen, Paul Rottger, et al.*2023 · 57 citations*](https://md.research.elamur.ai/free/en/papers/kirk-2023-personalisation-within-bounds-risk-taxonomy/)
52. **[The Multilingual Alignment Prism: Aligning Global and Local Preferences to Reduce Harm](https://md.research.elamur.ai/free/en/papers/aakanksha-2024-multilingual-alignment-prism-aligning-global/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Aakanksha, Arash Ahmadian, Beyza Ermis, et al.*2024 · 49 citations*
53. [**HyperCLOVA X Technical Report arXiv:2404.01954**Kang Min Yoo, Jaegeun Han, Sookyo In, et al.*2024 · 44 citations*](https://md.research.elamur.ai/free/en/papers/yoo-2024-hyperclova-x-technical-report/)
54. [**When does In-context Learning Fall Short and Why? A Study on Specification-Heavy Tasks arXiv:2311.08993**Hao Peng, Xiaozhi Wang, Jianhui Chen, et al.*2023 · 42 citations*](https://md.research.elamur.ai/free/en/papers/peng-2023-context-learning-fall-short-why/)
55. [**SALMON: Self-Alignment with Instructable Reward Models arXiv:2310.05910**Zhiqing Sun, Yikang Shen, Hongxin Zhang, et al.*2023 · 41 citations*](https://md.research.elamur.ai/free/en/papers/sun-2023-salmon-self-alignment-instructable-reward/)
56. **[Sociodemographic Bias in Language Models: A Survey and Forward Path](https://md.research.elamur.ai/free/en/papers/gupta-2023-sociodemographic-bias-language-models-survey/) [Workshop on Gender Bias in Natural Language Processing](https://md.research.elamur.ai/free/en/venues/gebnlp/)**Vipul Gupta, Pranav Narayanan Venkit, Shomir Wilson, et al.*2023 · 40 citations*
57. **[Aligning LLMs with Individual Preferences via Interaction](https://md.research.elamur.ai/free/en/papers/wu-2025-aligning-llms-individual-preferences-interaction/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Shujin Wu, Yi R. Fung, Cheng Qian, et al.*2025 · 24 citations*
58. [**Rewarding Chatbots for Real-World Engagement with Millions of Users arXiv:2303.06135**Robert Irvine, Douglas Boubert, Vyas Raina, et al.*2023 · 22 citations*](https://md.research.elamur.ai/free/en/papers/irvine-2023-rewarding-chatbots-real-world-engagement/)
59. **[CRAFT Your Dataset: Task-Specific Synthetic Dataset Generation Through Corpus Retrieval and Augmentation](https://md.research.elamur.ai/free/en/papers/ziegler-2025-craft-your-dataset-task-specific/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Ingo Ziegler, Abdullatif Köksal, Desmond Elliott, et al.*2025 · 20 citations*
60. **[The Dark Side of Function Calling: Pathways to Jailbreaking Large Language Models](https://md.research.elamur.ai/free/en/papers/wu-2025-dark-side-function-calling-pathways/) [International Conference on Computational Linguistics (COLING)](https://md.research.elamur.ai/free/en/venues/coling/)**Zihui Wu, Haichang Gao, Jianping He, et al.*2025 · 8 citations*
61. **[CoAct: Co-Active LLM Preference Learning with Human-AI Synergy](https://md.research.elamur.ai/free/en/papers/xu-2026-coact-co-active-llm-preference/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Ruiyao Xu, Mihir Parmar, Tiankai Yang, et al.*2026 · 1 citation*
62. **[Incentivizing Strong Reasoning from Weak Supervision](https://md.research.elamur.ai/free/en/papers/yuan-2026-incentivizing-strong-reasoning-weak-supervision/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Yige Yuan, Teng Xiao, Shuchang Tao, et al.*2026 · 1 citation*
63. **[When Do Large Language Models Exhibit Unsolicited Deception?](https://md.research.elamur.ai/free/en/papers/taylor-2026-when-do-large-language-models/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Samuel M. Taylor, Benjamin K. Bergen*2026 · 1 citation*
64. **[Entity-Level Sentiment Analysis with Sentence Relevance Detection](https://md.research.elamur.ai/free/en/papers/ronningstad-2026-entity-level-sentiment-analysis-sentence/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Egil Rønningstad, Roman Klinger, Lilja Øvrelid, et al.*2026*
65. **[Generalizing Trust: Weak-to-Strong Trustworthiness in Language Models](https://md.research.elamur.ai/free/en/papers/sun-2026-generalizing-trust-weak-strong-trustworthiness/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Lillian Sun, Martin Pawelczyk, Zhenting Qi, et al.*2026*
66. **[How Far Can Bias Go? Tracing Bias from Pre-Training Data to Alignment](https://md.research.elamur.ai/free/en/papers/thaler-2026-how-far-can-bias-go/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Marion Thaler, Abdullatif Köksal, Alina Leidinger, et al.*2026*
67. **[PubMed Reasoner: Dynamic Reasoning-based Retrieval for Evidence-Grounded Biomedical Question Answering](https://md.research.elamur.ai/free/en/papers/zhang-2026-pubmed-reasoner-dynamic-reasoning-based/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Yiqing Zhang, Xiaozhong Liu, Fabricio Murai*2026*
68. **[QueerGen: How LLMs Reflect Societal Norms on Gender and Sexuality in Sentence Completion Task](https://md.research.elamur.ai/free/en/papers/sosto-2026-queergen-how-llms-reflect-societal/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Mae Sosto, Delfina S. Martinez Pandiani, Laura Hollink*2026*
69. **[Too Open for Opinion? Embracing Open-Endedness in Large Language Models for Social Simulation](https://md.research.elamur.ai/free/en/papers/ma-2026-too-open-opinion-embracing-open/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Bolei Ma, Yong Cao, Indira Sen, et al.*2026*

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

- [← back to](https://md.research.elamur.ai/free/en/authors/vishal-maini/) — Vishal Maini