Awesome LLM Diversity

A curated collection of research papers exploring the generation diversity in Large Language Model. This repository tracks cutting-edge research on methods, evaluation, annalysis, and application. Research from all relative domains are welcome!

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Mode Collapse & Entropy

• RAGEN-2: Reasoning Collapse in Agentic RL [paper] 2026-04
  Zihan Wang, Chi Gui, Xing Jin, Qineng Wang, Licheng Liu, Kangrui Wang, Shiqi Chen, Linjie Li, Zhengyuan Yang, Pingyue Zhang, Yiping Lu, Jiajun Wu, Li Fei-Fei, Lijuan Wang, Yejin Choi, Manling Li.

• On the Entropy Dynamics in Reinforcement Fine-Tuning of Large Language Models [paper] 2026-02
  Shumin Wang, Yuexiang Xie, Wenhao Zhang, Yuchang Sun, Yanxi Chen, Yaliang Li, Yanyong Zhang.

• The Price of Format: Diversity Collapse in LLMs [paper] 2026-02
  Longfei Yun, Chenyang An, Zilong Wang, Letian Peng, Jingbo Shang.

• Exploration vs Exploitation: Rethinking RLVR through Clipping, Entropy, and Spurious Reward [paper] 2026-01
  Peter Chen, Xiaopeng Li, Ziniu Li, Wotao Yin, Xi Chen, Tianyi Lin.

• KL-Regularized Reinforcement Learning is Designed to Mode Collapse [paper] 2025-10
  Anthony GX-Chen, Jatin Prakash, Jeff Guo, Rob Fergus, Rajesh Ranganath.

• The Unreasonable Effectiveness of Entropy Minimization in LLM Reasoning [paper] 2025-10
  Shivam Agarwal, Zimin Zhang, Lifan Yuan, Jiawei Han, Hao Peng.

• Does Reinforcement Learning Really Incentivize Reasoning Capacity in LLMs Beyond the Base Model? [paper] 2025-10
  Yang Yue, Zhiqi Chen, Rui Lu, Andrew Zhao, Zhaokai Wang, Yang Yue, Shiji Song, Gao Huang.

• The Entropy Mechanism of Reinforcement Learning for Reasoning Language Models [paper] 2025-07
  Ganqu Cui, Yuchen Zhang, Jiacheng Chen, Lifan Yuan, Zhi Wang, Yuxin Zuo, Haozhan Li, Yuchen Fan, Huayu Chen, Weize Chen, Zhiyuan Liu, Hao Peng, Lei Bai, Wanli Ouyang, Yu Cheng, Bowen Zhou, Ning Ding.

• The Invisible Leash: Why RLVR May Not Escape Its Origin [paper] 2025-07
  Fang Wu, Weihao Xuan, Ximing Lu, Zaid Harchaoui, Yejin Choi.

• The Curious Decline of Linguistic Diversity: Training Language Models on Synthetic Text [paper] 2023-11
  Yanzhu Guo, Guokan Shang, Michalis Vazirgiannis, Chloé Clavel. ACL 2024.

Sampling & Decoding

• Time-Annealed Perturbation Sampling: Diverse Generation for Diffusion Language Models [paper] 2026-05
  Jingxuan Wu, Zhenglin Wan, Xingrui Yu, Yuzhe Yang, Yiqiao Huang, Ivor Tsang, Yang You.

• Inducing Sustained Creativity and Diversity in Large Language Models [paper] 2026-03
  Queenie Luo, Gary King, Michael Puett, Michael D. Smith.

• REAL Sampling: Boosting Factuality and Diversity of Open-ended Generation by Extrapolating the Entropy of an Infinitely Large LM [paper] 2025-10
  Haw-Shiuan Chang, Nanyun Peng, Mohit Bansal, Anil Ramakrishna, Tagyoung Chung.

• Verbalized Sampling: How to Mitigate Mode Collapse and Unlock LLM Diversity [paper] 2025-10
  Jiayi Zhang, Simon Yu, Derek Chong, Anthony Sicilia, Michael R. Tomz, Christopher D. Manning, Weiyan Shi.

• Top-H Decoding: Adapting the Creativity and Coherence with Bounded Entropy in Text Generation [paper] 2025-10
  Erfan Baghaei Potraghloo, Seyedarmin Azizi, Souvik Kundu, Massoud Pedram.

• EDT: Improving Large Language Models' Generation by Entropy-based Dynamic Temperature Sampling [paper] 2025-08
  Shimao Zhang, Yu Bao, Shujian Huang.

• Multiverse: Your Language Models Secretly Decide How to Parallelize and Merge Generation [paper] 2025-06
  Xinyu Yang, Yuwei An, Hongyi Liu, Tianqi Chen, Beidi Chen.

• Multilingual Prompting for Improving LLM Generation Diversity [paper] 2025-05
  Qihan Wang, Shidong Pan, Tal Linzen, Emily Black. EMNLP 2025.

• Flaming-hot Initiation with Regular Execution Sampling for Large Language Models [paper] 2024-10
  Weizhe Chen, Zhicheng Zhang, Guanlin Liu, Renjie Zheng, Wenlei Shi, Chen Dun, Zheng Wu, Xing Jin, Lin Yan.

• SimpleStrat: Diversifying Language Model Generation with Stratification [paper] 2024-10
  Justin Wong, Yury Orlovskiy, Michael Luo, Sanjit A. Seshia, Joseph E. Gonzalez.

• PAD: Personalized Alignment of LLMs at Decoding-Time [paper] 2024-10
  Ruizhe Chen, Xiaotian Zhang, Meng Luo, Wenhao Chai, Zuozhu Liu. ICLR 2025.

• Turning Up the Heat: Min-p Sampling for Creative and Coherent LLM Outputs [paper] 2024-07
  Minh Nhat Nguyen, Andrew Baker, Clement Neo, Allen Roush, Andreas Kirsch, Ravid Shwartz-Ziv. ICLR 2025.

• Improving Diversity of Commonsense Generation by Large Language Models via In-Context Learning [paper] 2024-04
  Tianhui Zhang, Bei Peng, Danushka Bollegala. EMNLP 2024.

• Forcing Diffuse Distributions out of Language Models [paper] 2024-04
  Yiming Zhang, Avi Schwarzschild, Nicholas Carlini, Zico Kolter, Daphne Ippolito.

• Partially Randomizing Transformer Weights for Dialogue Response Diversity [paper] 2023-11
  Jing Yang Lee, Kong Aik Lee, Woon-Seng Gan.

• Improving Diversity of Demographic Representation in Large Language Models via Collective-Critiques and Self-Voting [paper] 2023-10
  Preethi Lahoti, Nicholas Blumm, Xiao Ma, Raghavendra Kotikalapudi, Sahitya Potluri, Qijun Tan, Hansa Srinivasan, Ben Packer, Ahmad Beirami, Alex Beutel, Jilin Chen. EMNLP 2023.

• Language Model Crossover: Variation through Few-Shot Prompting [paper] 2023-02
  Elliot Meyerson, Mark J. Nelson, Herbie Bradley, Adam Gaier, Arash Moradi, Amy K. Hoover, Joel Lehman.

• Diverse Beam Search: Decoding Diverse Solutions from Neural Sequence Models [paper] 2016-10
  Ashwin K Vijayakumar, Michael Cogswell, Ramprasath R. Selvaraju, Qing Sun, Stefan Lee, David Crandall, Dhruv Batra. AAAI 2018.

Test-time Scaling

• No Single Best Model for Diversity: Learning a Router for Sample Diversity [paper] 2026-04
  Yuhan Liu, Fangyuan Xu, Vishakh Padmakumar, Daphne Ippolito, Eunsol Choi.

• Learning to Discover at Test Time [paper] 2026-01
  Mert Yuksekgonul, Daniel Koceja, Xinhao Li, Federico Bianchi, Jed McCaleb, Xiaolong Wang, Jan Kautz, Yejin Choi, James Zou, Carlos Guestrin, Yu Sun.

• Mode-Conditioning Unlocks Superior Test-Time Scaling [paper] 2025-11
  Chen Henry Wu, Sachin Goyal, Aditi Raghunathan.

• ThetaEvolve: Test-time Learning on Open Problems [paper] 2025-11
  Yiping Wang, Shao-Rong Su, Zhiyuan Zeng, Eva Xu, Liliang Ren, Xinyu Yang, Zeyi Huang, Xuehai He, Luyao Ma, Baolin Peng, Hao Cheng, Pengcheng He, Weizhu Chen, Shuohang Wang, Simon Shaolei Du, Yelong Shen.

• Deep Think with Confidence [paper] 2025-09
  Yichao Fu, Xuewei Wang, Yuandong Tian, Jiawei Zhao.

• Scalable Best-of-N Selection for Large Language Models via Self-Certainty [paper] 2025-08
  Zhewei Kang, Xuandong Zhao, Dawn Song.

• Optimizing Temperature for Language Models with Multi-Sample Inference [paper] 2025-02
  Weihua Du, Yiming Yang, Sean Welleck.

Supervised Training for Diversity

• Spectrum Tuning: Post-Training for Distributional Coverage and In-Context Steerability [paper] 2026-01
  Taylor Sorensen, Benjamin Newman, Jared Moore, Chan Park, Jillian Fisher, Niloofar Mireshghallah, Liwei Jiang, Yejin Choi.

• Preserving Diversity in Supervised Fine-Tuning of Large Language Models [paper] 2025-11
  Ziniu Li, Congliang Chen, Tian Xu, Zeyu Qin, Jiancong Xiao, Zhi-Quan Luo, Ruoyu Sun.

• Efficient Diversity-Preserving Diffusion Alignment via Gradient-Informed GFlowNets [paper] 2025-10
  Zhen Liu, Tim Z. Xiao, Weiyang Liu, Yoshua Bengio, Dinghuai Zhang.

• Flow of Reasoning: Training LLMs for Divergent Reasoning with Minimal Examples [paper] 2025-10
  Fangxu Yu, Lai Jiang, Haoqiang Kang, Shibo Hao, Lianhui Qin.

• GFlowNet Fine-tuning for Diverse Correct Solutions in Mathematical Reasoning Tasks [paper] 2025-08
  Ryoichi Takase, Masaya Tsunokake, Yuta Tsuchiya, Shota Inuzuka.

• GDPO: Learning to Directly Align Language Models with Diversity Using GFlowNets [paper] 2025-08
  Oh Joon Kwon, Daiki E. Matsunaga, Kee-Eung Kim.

• Flow Network based Generative Models for Non-Iterative Diverse Candidate Generation [paper] 2025-08
  Emmanuel Bengio, Moksh Jain, Maksym Korablyov, Doina Precup, Yoshua Bengio.

• Modifying Large Language Model Post-Training for Diverse Creative Writing [paper] 2025-03
  John Joon Young Chung, Vishakh Padmakumar, Melissa Roemmele, Yuqian Sun, Max Kreminski.

• Diverse Preference Optimization [paper] 2025-01
  Jack Lanchantin, Angelica Chen, Shehzaad Dhuliawala, Ping Yu, Jason Weston, Sainbayar Sukhbaatar, Ilia Kulikov.

• Improving Linguistic Diversity of Large Language Models with Possibility Exploration Fine-Tuning [paper] 2024-12
  Long Mai, Julie Carson-Berndsen.

• Beyond Reverse KL: Generalizing Direct Preference Optimization with Diverse Divergence Constraints [paper] 2023-09
  Chaoqi Wang, Yibo Jiang, Chenghao Yang, Han Liu, Yuxin Chen.

• Model soups: averaging weights of multiple fine-tuned models improves accuracy without increasing inference time [paper] 2022-03
  Mitchell Wortsman, Gabriel Ilharco, Samir Yitzhak Gadre, Rebecca Roelofs, Raphael Gontijo-Lopes, Ari S. Morcos, Hongseok Namkoong, Ali Farhadi, Yair Carmon, Simon Kornblith, Ludwig Schmidt. ICML 2022.

• Diversify and Disambiguate: Learning From Underspecified Data [paper] 2022-02
  Yoonho Lee, Huaxiu Yao, Chelsea Finn. ICLR 2023.

• A Distributional Approach to Controlled Text Generation [paper] 2020-12
  Muhammad Khalifa, Hady Elsahar, Marc Dymetman. ICLR 2021.

RL Training for Diversity

• UpSkill: Mutual Information Skill Learning for Structured Response Diversity in LLMs [paper] 2026-05
  Devan Shah, Owen Yang, Daniel Yang, Chongyi Zheng, Benjamin Eysenbach.

• Quality-Diversity through AI Feedback [paper] 2026-04
  Herbie Bradley, Andrew Dai, Hannah Teufel, Jenny Zhang, Koen Oostermeijer, Marco Bellagente, Jeff Clune, Kenneth Stanley, Grégory Schott, Joel Lehman.

• Diverse Preference Learning for Capabilities and Alignment [paper] 2026-02
  Stewart Slocum, Asher Parker-Sartori, Dylan Hadfield-Menell.

• Can LLMs Guide Their Own Exploration? Gradient-Guided Reinforcement Learning for LLM Reasoning [paper] 2025-12
  Zhenwen Liang, Sidi Lu, Wenhao Yu, Kishan Panaganti, Yujun Zhou, Haitao Mi, Dong Yu.

• Optimizing Safe and Aligned Language Generation: A Multi-Objective GRPO Approach [paper] 2025-10
  Xuying Li, Zhuo Li, Yuji Kosuga, Victor Bian.

• Jointly Reinforcing Diversity and Quality in Language Model Generations [paper] 2025-09
  Tianjian Li, Yiming Zhang, Ping Yu, Swarnadeep Saha, Daniel Khashabi, Jason Weston, Jack Lanchantin, Tianlu Wang.

• Creative Preference Optimization [paper] 2025-05
  Mete Ismayilzada, Antonio Laverghetta Jr., Simone A. Luchini, Reet Patel, Antoine Bosselut, Lonneke van der Plas, Roger Beaty.

• Preference-Controlled Multi-Objective Reinforcement Learning for Conditional Text Generation [paper] 2023-11
  Wenqing Chen, Jidong Tian, Caoyun Fan, Yitian Li, Hao He, Yaohui Jin.

• Iteratively Learn Diverse Strategies with State Distance Information [paper] 2023-10
  Wei Fu, Weihua Du, Jingwei Li, Sunli Chen, Jingzhao Zhang, Yi Wu.

• Rewarded soups: towards Pareto-optimal alignment by interpolating weights fine-tuned on diverse rewards [paper] 2023-06
  Alexandre Ramé, Guillaume Couairon, Mustafa Shukor, Corentin Dancette, Jean-Baptiste Gaya, Laure Soulier, Matthieu Cord.

• Aligning Language Models with Preferences through f-divergence Minimization [paper] 2023-02
  Dongyoung Go, Tomasz Korbak, Germán Kruszewski, Jos Rozen, Nahyeon Ryu, Marc Dymetman.

Data & Pretraining

• Harnessing Diversity for Important Data Selection in Pretraining Large Language Models [paper] 2026-05
  Chi Zhang, Huaping Zhong, Kuan Zhang, Chengliang Chai, Rui Wang, Xinlin Zhuang, Tianyi Bai, Jiantao Qiu, Lei Cao, Ju Fan, Ye Yuan, Guoren Wang, Conghui He.

• BARE: Leveraging Base Language Models for Few-Shot Synthetic Data Generation [paper] 2025-10
  Alan Zhu, Parth Asawa, Jared Quincy Davis, Lingjiao Chen, Boris Hanin, Ion Stoica, Joseph E. Gonzalez, Matei Zaharia.

• GenQA: Generating Millions of Instructions from a Handful of Prompts [paper] 2024-06
  Jiuhai Chen, Rifaa Qadri, Yuxin Wen, Neel Jain, John Kirchenbauer, Tianyi Zhou, Tom Goldstein.

• Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias [paper] 2023-06
  Yue Yu, Yuchen Zhuang, Jieyu Zhang, Yu Meng, Alexander Ratner, Ranjay Krishna, Jiaming Shen, Chao Zhang. NeurIPS 2023.

• WizardLM: Empowering large pre-trained language models to follow complex instructions [paper] 2023-04
  Can Xu, Qingfeng Sun, Kai Zheng, Xiubo Geng, Pu Zhao, Jiazhan Feng, Chongyang Tao, Qingwei Lin, Daxin Jiang.

Metrics & Measurement

• Death of the Novel(ty): Beyond n-Gram Novelty as a Metric for Textual Creativity [paper] 2025-10
  Arkadiy Saakyan, Najoung Kim, Smaranda Muresan, Tuhin Chakrabarty.

• Standardizing the Measurement of Text Diversity: A Tool and a Comparative Analysis of Scores [paper] 2025-10
  Chantal Shaib, Joe Barrow, Jiuding Sun, Alexa F. Siu, Byron C. Wallace, Ani Nenkova.

• Detection and Measurement of Syntactic Templates in Generated Text [paper] 2025-10
  Chantal Shaib, Yanai Elazar, Junyi Jessy Li, Byron C. Wallace.

• Measuring AI "Slop" in Text [paper] 2025-09
  Chantal Shaib, Tuhin Chakrabarty, Diego Garcia-Olano, Byron C. Wallace.

• Benchmarking Linguistic Diversity of Large Language Models [paper] 2025-08
  Yanzhu Guo, Guokan Shang, Chloé Clavel.

• Measuring Data Diversity for Instruction Tuning: A Systematic Analysis and A Reliable Metric [paper] 2025-08
  Yuming Yang, Yang Nan, Junjie Ye, Shihan Dou, Xiao Wang, Shuo Li, Huijie Lv, Mingqi Wu, Tao Gui, Qi Zhang, Xuanjing Huang.

• Rethinking and Refining the Distinct Metric [paper] 2025-07
  Siyang Liu, Sahand Sabour, Yinhe Zheng, Pei Ke, Xiaoyan Zhu, Minlie Huang.

• The Vendi Score: A Diversity Evaluation Metric for Machine Learning [paper] 2025-07
  Dan Friedman, Adji Bousso Dieng.

• Evaluating the Diversity and Quality of LLM Generated Content [paper] 2025-04
  Alexander Shypula, Shuo Li, Botong Zhang, Vishakh Padmakumar, Kayo Yin, Osbert Bastani. COLM 2025.

• NoveltyBench: Evaluating Language Models for Humanlike Diversity [paper] 2025-04
  Yiming Zhang, Harshita Diddee, Susan Holm, Hanchen Liu, Xinyue Liu, Vinay Samuel, Barry Wang, Daphne Ippolito.

• Variance reduction in output from generative AI [paper] 2025-03
  Yu Xie, Yueqi Xie.

• Artificial Hivemind: The Open-Ended Homogeneity of Language Models (and Beyond) [paper] 2025
  Liwei Jiang, Yuanjun Chai, Margaret Li, Mickel Liu, Raymond Fok, Nouha Dziri, Yulia Tsvetkov, Maarten Sap, Yejin Choi. NeurIPS 2025.

• Every Answer Matters: Evaluating Commonsense with Probabilistic Measures [paper] 2024-06
  Qi Cheng, Michael Boratko, Pranay Kumar Yelugam, Tim O'Gorman, Nalini Singh, Andrew McCallum, Xiang Lorraine Li. ACL 2024.

• Exploring Precision and Recall to assess the quality and diversity of LLMs [paper] 2024-02
  Florian Le Bronnec, Alexandre Verine, Benjamin Negrevergne, Yann Chevaleyre, Alexandre Allauzen. ACL 2024.

• Unifying Human and Statistical Evaluation for Natural Language Generation [paper] 2023-11
  Tatsunori B. Hashimoto, Hugh Zhang, Percy Liang.

• Semantic Diversity in Dialogue with Natural Language Inference [paper] 2023-11
  Katherine Stasaski, Marti Hearst.

• DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks [paper] 2023-09
  Kaijie Zhu, Jiaao Chen, Jindong Wang, Neil Zhenqiang Gong, Diyi Yang, Xing Xie. ICLR 2024.

• Evaluating the Moral Beliefs Encoded in LLMs [paper] 2023-07
  Nino Scherrer, Claudia Shi, Amir Feder, David M. Blei.

• Towards Measuring the Representation of Subjective Global Opinions in Language Models [paper] 2023-06
  Esin Durmus, Karina Nguyen, Thomas I. Liao, Nicholas Schiefer, Amanda Askell, Anton Bakhtin, Carol Chen, Zac Hatfield-Dodds, Danny Hernandez, Nicholas Joseph, Liane Lovitt, Sam McCandlish, Orowa Sikder, Alex Tamkin, Janel Thamkul, Jared Kaplan, Jack Clark, Deep Ganguli.

• Pragmatically Appropriate Diversity for Dialogue Evaluation [paper] 2023-04
  Katherine Stasaski, Marti A. Hearst.

• Measuring and Improving Semantic Diversity of Dialogue Generation [paper] 2022-10
  Seungju Han, Beomsu Kim, Buru Chang.

• Semantic Diversity in Dialogue with Natural Language Inference [paper] 2022-05
  Katherine Stasaski, Marti A. Hearst. ACL 2022.

• Unifying Human and Statistical Evaluation for Natural Language Generation [paper] 2019-04
  Tatsunori B. Hashimoto, Hugh Zhang, Percy Liang.

Analysis & Theory

• SpecEval: Evaluating Model Adherence to Behavior Specifications [paper] 2026-01
  Ahmed Ahmed, Kevin Klyman, Yi Zeng, Sanmi Koyejo, Percy Liang.

• Rethinking the Evaluation of Alignment Methods: Insights into Diversity, Generalisation, and Safety [paper] 2025-10
  Denis Janiak, Julia Moska, Dawid Motyka, Karolina Seweryn, Paweł Walkowiak, Bartosz Żuk, Arkadiusz Janz.

• Learning the Wrong Lessons: Syntactic-Domain Spurious Correlations in Language Models [paper] 2025-10
  Chantal Shaib, Vinith M. Suriyakumar, Levent Sagun, Byron C. Wallace, Marzyeh Ghassemi.

• LoGU: Long-form Generation with Uncertainty Expressions [paper] 2025-08
  Ruihan Yang, Caiqi Zhang, Zhisong Zhang, Xinting Huang, Sen Yang, Nigel Collier, Dong Yu, Deqing Yang.

• Revisiting LLM Reasoning via Information Bottleneck [paper] 2025-08
  Shiye Lei, Zhihao Cheng, Kai Jia, Dacheng Tao.

• How Random is Random? Evaluating the Randomness and Humaness of LLMs' Coin Flips [paper] 2025-07
  Katherine Van Koevering, Jon Kleinberg.

• Language Models (Mostly) Know What They Know [paper] 2025-07
  Saurav Kadavath, Tom Conerly, Amanda Askell, Tom Henighan, Dawn Drain, Ethan Perez, Nicholas Schiefer, Zac Hatfield-Dodds, Nova DasSarma, Eli Tran-Johnson, Scott Johnston, Sheer El-Showk, Andy Jones, Nelson Elhage, Tristan Hume, Anna Chen, Yuntao Bai, Sam Bowman, Stanislav Fort, Deep Ganguli, Danny Hernandez, Josh Jacobson, Jackson Kernion, Shauna Kravec, Liane Lovitt, Kamal Ndousse, Catherine Olsson, Sam Ringer, Dario Amodei, Tom Brown, Jack Clark, Nicholas Joseph, Ben Mann, Sam McCandlish, Chris Olah, Jared Kaplan.

• Correlated Errors in Large Language Models [paper] 2025-07
  Elliot Kim, Avi Garg, Kenny Peng, Nikhil Garg.

• Contextualized Evaluations: Judging Language Model Responses to Underspecified Queries [paper] 2025-07
  Chaitanya Malaviya, Joseph Chee Chang, Dan Roth, Mohit Iyyer, Mark Yatskar, Kyle Lo.

• Base Models Beat Aligned Models at Randomness and Creativity [paper] 2025-04
  Peter West, Christopher Potts.

• (How) Can Transformers Predict Pseudo-Random Numbers? [paper] 2025-02
  Tao Tao, Darshil Doshi, Dayal Singh Kalra, Tianyu He, Maissam Barkeshli.

• What Evidence Do Language Models Find Convincing? [paper] 2024-10
  Alexander Wan, Eric Wallace, Dan Klein.

• What Evidence Do Language Models Find Convincing? [paper] 2024-02
  Alexander Wan, Eric Wallace, Dan Klein. ACL 2024.

• Measurement in the Age of LLMs: An Application to Ideological Scaling [paper] 2023-12
  Sean O'Hagan, Aaron Schein. NeurIPS 2023.

• The Earth is Flat because...: Investigating LLMs' Belief towards Misinformation via Persuasive Conversation [paper] 2023-12
  Rongwu Xu, Brian S. Lin, Shujian Yang, Tianqi Zhang, Weiyan Shi, Tianwei Zhang, Zhixuan Fang, Wei Xu, Han Qiu.

• Understanding the Effects of RLHF on LLM Generalisation and Diversity [paper] 2023-10
  Robert Kirk, Ishita Mediratta, Christoforos Nalmpantis, Jelena Luketina, Eric Hambro, Edward Grefenstette, Roberta Raileanu.

• The Empty Signifier Problem: Towards Clearer Paradigms for Operationalising "Alignment" in Large Language Models [paper] 2023-10
  Hannah Rose Kirk, Bertie Vidgen, Paul Röttger, Scott A. Hale.

• Uncertainty in Natural Language Generation: From Theory to Applications [paper] 2023-07
  Joris Baan, Nico Daheim, Evgenia Ilia, Dennis Ulmer, Haau-Sing Li, Raquel Fernández, Barbara Plank, Rico Sennrich, Chrysoula Zerva, Wilker Aziz.

• Generating with Confidence: Uncertainty Quantification for Black-box Large Language Models [paper] 2023-05
  Zhen Lin, Shubhendu Trivedi, Jimeng Sun.

• What Comes Next? Evaluating Uncertainty in Neural Text Generators Against Human Production Variability [paper] 2023-05
  Mario Giulianelli, Joris Baan, Wilker Aziz, Raquel Fernández, Barbara Plank. EMNLP 2023.

• Semantic uncertainty guides the extension of conventions to new referents [paper] 2023-05
  Ron Eliav, Anya Ji, Yoav Artzi, Robert D. Hawkins.

Alignment & Preference

• PrefPalette: Personalized Preference Modeling with Latent Attributes [paper] 2025-07
  Shuyue Stella Li, Melanie Sclar, Hunter Lang, Ansong Ni, Jacqueline He, Puxin Xu, Andrew Cohen, Chan Young Park, Yulia Tsvetkov, Asli Celikyilmaz.

• SPARTA ALIGNMENT: Collectively Aligning Multiple Language Models through Combat [paper] 2025-06
  Yuru Jiang, Wenxuan Ding, Shangbin Feng, Greg Durrett, Yulia Tsvetkov.

• Preference Optimization with Multi-Sample Comparisons [paper] 2024-10
  Chaoqi Wang, Zhuokai Zhao, Chen Zhu, Karthik Abinav Sankararaman, Michal Valko, Xuefei Cao, Zhaorun Chen, Madian Khabsa, Yuxin Chen, Hao Ma, Sinong Wang.

• Can Language Models Reason about Individualistic Human Values and Preferences? [paper] 2024-10
  Liwei Jiang, Taylor Sorensen, Sydney Levine, Yejin Choi. ACL 2025.

• Aligning to Thousands of Preferences via System Message Generalization [paper] 2024-05
  Seongyun Lee, Sue Hyun Park, Seungone Kim, Minjoon Seo. NeurIPS 2024.

• MetaAligner: Towards Generalizable Multi-Objective Alignment of Language Models [paper] 2024-03
  Kailai Yang, Zhiwei Liu, Qianqian Xie, Jimin Huang, Tianlin Zhang, Sophia Ananiadou. NeurIPS 2024.

• Distributional Preference Learning: Understanding and Accounting for Hidden Context in RLHF [paper] 2023-12
  Anand Siththaranjan, Cassidy Laidlaw, Dylan Hadfield-Menell. ICLR 2024.

• Everyone Deserves A Reward: Learning Customized Human Preferences [paper] 2023-09
  Pengyu Cheng, Jiawen Xie, Ke Bai, Yong Dai, Nan Du.

Pluralism & Social Choice

• Arrow’s Theorem [paper] 2024-11
  Michael Morreau.

• Iterative ranking from pair-wise comparisons [paper] 2024-11
  Sahand Negahban, Sewoong Oh, Devavrat Shah.

• Biased AI can Influence Political Decision-Making [paper] 2024-10
  Jillian Fisher, Shangbin Feng, Robert Aron, Thomas Richardson, Yejin Choi, Daniel W. Fisher, Jennifer Pan, Yulia Tsvetkov, Katharina Reinecke.

• From Distributional to Overton Pluralism: Investigating Large Language Model Alignment [paper] 2024-06
  Thom Lake, Eunsol Choi, Greg Durrett. ACL 2025.

• Modular Pluralism: Pluralistic Alignment via Multi-LLM Collaboration [paper] 2024-06
  Shangbin Feng, Taylor Sorensen, Yuhan Liu, Jillian Fisher, Chan Young Park, Yejin Choi, Yulia Tsvetkov. EMNLP 2024.

• The PRISM Alignment Dataset: What Participatory, Representative and Individualised Human Feedback Reveals About the Subjective and Multicultural Alignment of Large Language Models [paper] 2024-04
  Hannah Rose Kirk, Alexander Whitefield, Paul Röttger, Andrew Bean, Katerina Margatina, Juan Ciro, Rafael Mosquera, Max Bartolo, Adina Williams, He He, Bertie Vidgen, Scott A. Hale.

• Social Choice Should Guide AI Alignment in Dealing with Diverse Human Feedback [paper] 2024-04
  Vincent Conitzer, Rachel Freedman, Jobst Heitzig, Wesley H. Holliday, Bob M. Jacobs, Nathan Lambert, Milan Mossé, Eric Pacuit, Stuart Russell, Hailey Schoelkopf, Emanuel Tewolde, William S. Zwicker.

• A Roadmap to Pluralistic Alignment [paper] 2024-02
  Taylor Sorensen, Jared Moore, Jillian Fisher, Mitchell Gordon, Niloofar Mireshghallah, Christopher Michael Rytting, Andre Ye, Liwei Jiang, Ximing Lu, Nouha Dziri, Tim Althoff, Yejin Choi. ICML 2024.

• Evaluating Agents using Social Choice Theory [paper] 2023-12
  Marc Lanctot, Kate Larson, Yoram Bachrach, Luke Marris, Zun Li, Avishkar Bhoopchand, Thomas Anthony, Brian Tanner, Anna Koop.

• How Far Can We Extract Diverse Perspectives from Large Language Models? [paper] 2023-11
  Shirley Anugrah Hayati, Minhwa Lee, Dheeraj Rajagopal, Dongyeop Kang. EMNLP 2024.

• AI Alignment and Social Choice: Fundamental Limitations and Policy Implications [paper] 2023-10
  Abhilash Mishra.

• Value Kaleidoscope: Engaging AI with Pluralistic Human Values, Rights, and Duties [paper] 2023-09
  Taylor Sorensen, Liwei Jiang, Jena Hwang, Sydney Levine, Valentina Pyatkin, Peter West, Nouha Dziri, Ximing Lu, Kavel Rao, Chandra Bhagavatula, Maarten Sap, John Tasioulas, Yejin Choi.

• Whose Opinions Do Language Models Reflect? [paper] 2023-03
  Shibani Santurkar, Esin Durmus, Faisal Ladhak, Cinoo Lee, Percy Liang, Tatsunori Hashimoto.

• Convergence Voting: From Pairwise Comparisons to Consensus [paper] 2021-02
  Gergei Bana, Wojciech Jamroga, David Naccache, Peter Y. A. Ryan.

• Rank Centrality: Ranking from Pair-wise Comparisons [paper] 2012-09
  Sahand Negahban, Sewoong Oh, Devavrat Shah.

Reasoning & Problem Solving

• Diversity as the bottleneck in Self-Play [paper] 2026-05
  Hamish Ivison.

• AlphaEvolve: A Gemini-powered coding agent for designing advanced algorithms [paper] 2026-04
  AlphaEvolve team.

• AdaExplore: Failure-Driven Adaptation and Diversity-Preserving Search for Efficient Kernel Generation [paper] 2026-04
  Weihua Du, Jingming Zhuo, Yixin Dong, Andre Wang He, Weiwei Sun, Zeyu Zheng, Manupa Karunaratne, Ivan Fox, Tim Dettmers, Tianqi Chen, Yiming Yang, Sean Welleck.

• RAGEN: Understanding Self-Evolution in LLM Agents via Multi-Turn Reinforcement Learning [paper] 2026-04
  Zihan Wang, Kangrui Wang, Qineng Wang, Pingyue Zhang, Linjie Li, Zhengyuan Yang, Xing Jin, Kefan Yu, Minh Nhat Nguyen, Licheng Liu, Eli Gottlieb, Yiping Lu, Kyunghyun Cho, Jiajun Wu, Li Fei-Fei, Lijuan Wang, Yejin Choi, Manling Li.

• R-Diverse: Mitigating Diversity Illusion in Self-Play LLM Training [paper] 2026-04
  Gengsheng Li, Jinghan He, Shijie Wang, Dan Zhang, Ruiqi Liu, Renrui Zhang, Zijun Yao, Junfeng Fang, Haiyun Guo, Jinqiao Wang.

• EvoX: Meta-Evolution for Automated Discovery [paper] 2026-02
  Shu Liu, Shubham Agarwal, Monishwaran Maheswaran, Mert Cemri, Zhifei Li, Qiuyang Mang, Ashwin Naren, Ethan Boneh, Audrey Cheng, Melissa Z. Pan, Alexander Du, Kurt Keutzer, Alvin Cheung, Alexandros G. Dimakis, Koushik Sen, Matei Zaharia, Ion Stoica.

• Aletheia tackles FirstProof autonomously [paper] 2026-02
  Tony Feng, Junehyuk Jung, Sang-hyun Kim, Carlo Pagano, Sergei Gukov, Chiang-Chiang Tsai, David Woodruff, Adel Javanmard, Aryan Mokhtari, Dawsen Hwang, Yuri Chervonyi, Jonathan N. Lee, Garrett Bingham, Trieu H. Trinh, Vahab Mirrokni, Quoc V. Le, Thang Luong.

• Calibrate-Then-Act: Cost-Aware Exploration in LLM Agents [paper] 2026-02
  Wenxuan Ding, Nicholas Tomlin, Greg Durrett.

• The Single-Multi Evolution Loop for Self-Improving Model Collaboration Systems [paper] 2026-02
  Shangbin Feng, Kishan Panaganti, Yulia Tsvetkov, Wenhao Yu.

• Reasoning Path Divergence: A New Metric and Curation Strategy to Unlock LLM Diverse Thinking [paper] 2025-11
  Feng Ju, Zeyu Qin, Rui Min, Zhitao He, Lingpeng Kong, Yi R. Fung.

• Diversity of Thought Improves Reasoning Abilities of LLMs [paper] 2025-11
  Ranjita Naik, Varun Chandrasekaran, Mert Yuksekgonul, Hamid Palangi, Besmira Nushi.

• Beyond Pass@1: Self-Play with Variational Problem Synthesis Sustains RLVR [paper] 2025-10
  Xiao Liang, Zhongzhi Li, Yeyun Gong, Yelong Shen, Ying Nian Wu, Zhijiang Guo, Weizhu Chen.

• No Free Lunch: Rethinking Internal Feedback for LLM Reasoning [paper] 2025-08
  Yanzhi Zhang, Zhaoxi Zhang, Haoxiang Guan, Yilin Cheng, Yitong Duan, Chen Wang, Yue Wang, Shuxin Zheng, Jiyan He.

• Can Large Language Models Invent Algorithms to Improve Themselves?: Algorithm Discovery for Recursive Self-Improvement through Reinforcement Learning [paper] 2024-10
  Yoichi Ishibashi, Taro Yano, Masafumi Oyamada. ACL 2025.

• Chain-of-Thought Reasoning Without Prompting [paper] 2024-02
  Xuezhi Wang, Denny Zhou.

• Enhancing Large Language Models Against Inductive Instructions with Dual-critique Prompting [paper] 2023-05
  Rui Wang, Hongru Wang, Fei Mi, Yi Chen, Boyang Xue, Kam-Fai Wong, Ruifeng Xu.

Creative Generation

• Reverse-Engineered Reasoning for Open-Ended Generation [paper] 2026-01
  Haozhe Wang, Haoran Que, Qixin Xu, Minghao Liu, Wangchunshu Zhou, Jiazhan Feng, Wanjun Zhong, Wei Ye, Tong Yang, Wenhao Huang, Ge Zhang, Fangzhen Lin.

• Echoes in AI: Quantifying lack of plot diversity in LLM outputs [paper] 2025-10
  Weijia Xu, Nebojsa Jojic, Sudha Rao, Chris Brockett, Bill Dolan.

• LitBench: A Benchmark and Dataset for Reliable Evaluation of Creative Writing [paper] 2025-07
  Daniel Fein, Sebastian Russo, Violet Xiang, Kabir Jolly, Rafael Rafailov, Nick Haber.

• Measuring Creative Writing with the Storyboard Task: The Role of Effort and Story Length [paper] 2025-01
  Christa L. Taylor, James C. Kaufman, Baptiste Barbot.

• Benchmarking Language Model Creativity: A Case Study on Code Generation [paper] 2024-07
  Yining Lu, Dixuan Wang, Tianjian Li, Dongwei Jiang, Sanjeev Khudanpur, Meng Jiang, Daniel Khashabi.

• MacGyver: Are Large Language Models Creative Problem Solvers? [paper] 2023-11
  Yufei Tian, Abhilasha Ravichander, Lianhui Qin, Ronan Le Bras, Raja Marjieh, Nanyun Peng, Yejin Choi, Thomas L. Griffiths, Faeze Brahman. ACL 2024.

• A Confederacy of Models: a Comprehensive Evaluation of LLMs on Creative Writing [paper] 2023-10
  Carlos Gómez-Rodríguez, Paul Williams. EMNLP 2023.

• Art or Artifice? Large Language Models and the False Promise of Creativity [paper] 2023-09
  Tuhin Chakrabarty, Philippe Laban, Divyansh Agarwal, Smaranda Muresan, Chien-Sheng Wu. CHI 2024.

Societal Impact

• Artificial Intelligence Tools Expand Scientists’ Impact but Contract Science’s Focus [paper] 2026
  Qianyue Hao, Fengli Xu, Yong Li, James Evans. Nature.

• Homogenization Effects of Large Language Models on Human Creative Ideation [paper] 2025-10
  Barrett R Anderson, Jash Hemant Shah, Max Kreminski.

• Generative artificial intelligence enhances creativity but reduces the diversity of novel content [paper] 2025-10
  Anil R. Doshi, Oliver P. Hauser.

• Leveraging AI for democratic discourse: Chat interventions can improve online political conversations at scale [paper] 2024-11
  Lisa P. Argyle, Christopher A. Bail, Ethan C. Busby, Joshua R. Gubler, Thomas Howe, Christopher Rytting, Taylor Sorensen, David Wingate.

• Psychology's WEIRD Problems [paper] 2024-10
  Guilherme Sanches de Oliveira, Edward Baggs.

• AI and the Problem of Knowledge Collapse [paper] 2024-04
  Andrew J. Peterson.

Cross-Cultural & Multilingual

• CARE: Assessing the Impact of Multilingual Human Preference Learning on Cultural Awareness [paper] 2025-04
  Geyang Guo, Tarek Naous, Hiromi Wakaki, Yukiko Nishimura, Yuki Mitsufuji, Alan Ritter, Wei Xu.

• CAVA: A Tool for Cultural Alignment Visualization & Analysis [paper] 2025-01
  Nevan Giuliani, Cheng Charles Ma, Prakruthi Pradeep, Daphne Ippolito.

• Challenges and Strategies in Cross-Cultural NLP [paper] 2024-11
  Daniel Hershcovich, Stella Frank, Heather Lent, Miryam de Lhoneux, Mostafa Abdou, Stephanie Brandl, Emanuele Bugliarello, Laura Cabello Piqueras, Ilias Chalkidis, Ruixiang Cui, Constanza Fierro, Katerina Margatina, Phillip Rust, Anders Søgaard.

• Evaluating Cultural and Social Awareness of LLM Web Agents [paper] 2024-10
  Haoyi Qiu, Alexander R. Fabbri, Divyansh Agarwal, Kung-Hsiang Huang, Sarah Tan, Nanyun Peng, Chien-Sheng Wu. ACL 2025.

• EnCBP: A New Benchmark Dataset for Finer-Grained Cultural Background Prediction in English [paper] 2024-10
  Weicheng Ma, Samiha Datta, Lili Wang, Soroush Vosoughi.

• Hate Speech Classifiers are Culturally Insensitive [paper] 2024-10
  Nayeon Lee, Chani Jung, Alice Oh.

• CulturalBench: A Robust, Diverse, and Challenging Cultural Benchmark by Human-AI CulturalTeaming [paper] 2024-10
  Yu Ying Chiu, Liwei Jiang, Bill Yuchen Lin, Chan Young Park, Shuyue Stella Li, Sahithya Ravi, Mehar Bhatia, Maria Antoniak, Yulia Tsvetkov, Vered Shwartz, Yejin Choi. ACL 2025.

• CIVICS: Building a Dataset for Examining Culturally-Informed Values in Large Language Models [paper] 2024-05
  Giada Pistilli, Alina Leidinger, Yacine Jernite, Atoosa Kasirzadeh, Alexandra Sasha Luccioni, Margaret Mitchell.

• CultureBank: An Online Community-Driven Knowledge Base Towards Culturally Aware Language Technologies [paper] 2024-04
  Weiyan Shi, Ryan Li, Yutong Zhang, Caleb Ziems, Chunhua yu, Raya Horesh, Rogério Abreu de Paula, Diyi Yang.

• EtiCor: Corpus for Analyzing LLMs for Etiquettes [paper] 2023-10
  Ashutosh Dwivedi, Pradhyumna Lavania, Ashutosh Modi. EMNLP 2023.

• Global Voices, Local Biases: Socio-Cultural Prejudices across Languages [paper] 2023-10
  Anjishnu Mukherjee, Chahat Raj, Ziwei Zhu, Antonios Anastasopoulos. EMNLP 2023.

• CulturaX: A Cleaned, Enormous, and Multilingual Dataset for Large Language Models in 167 Languages [paper] 2023-09
  Thuat Nguyen, Chien Van Nguyen, Viet Dac Lai, Hieu Man, Nghia Trung Ngo, Franck Dernoncourt, Ryan A. Rossi, Thien Huu Nguyen.

• BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language Models [paper] 2023-09
  Wei Qi Leong, Jian Gang Ngui, Yosephine Susanto, Hamsawardhini Rengarajan, Kengatharaiyer Sarveswaran, William Chandra Tjhi.

• SeaEval for Multilingual Foundation Models: From Cross-Lingual Alignment to Cultural Reasoning [paper] 2023-09
  Bin Wang, Zhengyuan Liu, Xin Huang, Fangkai Jiao, Yang Ding, AiTi Aw, Nancy F. Chen. ACL 2024.

• Multi-lingual and Multi-cultural Figurative Language Understanding [paper] 2023-05
  Anubha Kabra, Emmy Liu, Simran Khanuja, Alham Fikri Aji, Genta Indra Winata, Samuel Cahyawijaya, Anuoluwapo Aremu, Perez Ogayo, Graham Neubig. ACL 2023.

• SeeGULL: A Stereotype Benchmark with Broad Geo-Cultural Coverage Leveraging Generative Models [paper] 2023-05
  Akshita Jha, Aida Davani, Chandan K. Reddy, Shachi Dave, Vinodkumar Prabhakaran, Sunipa Dev.

• EnCBP: A New Benchmark Dataset for Finer-Grained Cultural Background Prediction in English [paper] 2022-03
  Weicheng Ma, Samiha Datta, Lili Wang, Soroush Vosoughi. ACL 2022.

• Challenges and Strategies in Cross-Cultural NLP [paper] 2022-03
  Daniel Hershcovich, Stella Frank, Heather Lent, Miryam de Lhoneux, Mostafa Abdou, Stephanie Brandl, Emanuele Bugliarello, Laura Cabello Piqueras, Ilias Chalkidis, Ruixiang Cui, Constanza Fierro, Katerina Margatina, Phillip Rust, Anders Søgaard. ACL 2022.

Human-Centered

• Does Writing with Language Models Reduce Content Diversity? [paper] 2023-09
  Vishakh Padmakumar, He He. ICLR 2024.

• Artificial Artificial Artificial Intelligence: Crowd Workers Widely Use Large Language Models for Text Production Tasks [paper] 2023-06
  Veniamin Veselovsky, Manoel Horta Ribeiro, Robert West.

• Factors Influencing Perceived Fairness in Algorithmic Decision-Making: Algorithm Outcomes, Development Procedures, and Individual Differences [paper] 2020-01
  Ruotong Wang, F. Maxwell Harper, Haiyi Zhu. CHI 2020.

Application

• Principled Content Selection to Generate Diverse and Personalized Multi-Document Summaries [paper] 2025-10
  Vishakh Padmakumar, Zichao Wang, David Arbour, Jennifer Healey.

• Exploring and Controlling Diversity in LLM-Agent Conversation [paper] 2024-12
  KuanChao Chu, Yi-Pei Chen, Hideki Nakayama. EMNLP 2025.

• SOTOPIA: Interactive Evaluation for Social Intelligence in Language Agents [paper] 2023-10
  Xuhui Zhou, Hao Zhu, Leena Mathur, Ruohong Zhang, Haofei Yu, Zhengyang Qi, Louis-Philippe Morency, Yonatan Bisk, Daniel Fried, Graham Neubig, Maarten Sap.

• ChatGPT to Replace Crowdsourcing of Paraphrases for Intent Classification: Higher Diversity and Comparable Model Robustness [paper] 2023-05
  Jan Cegin, Jakub Simko, Peter Brusilovsky. EMNLP 2023.

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Contributions

We thank the contributors to this paper list: Chenghao Yang (UChicago), Tenghao Huang (USC), Xinyue Liu (Stony Brook), Queenie Luo (Harvard).

This list is maintained by Yichen (Zach) Wang and organized by the awesome-paperlist-maintainer. Last updated June 19, 2026.