@misc{chakrabarty2024artartificelargelanguage,
      title={Art or Artifice? Large Language Models and the False Promise of Creativity}, 
      author={Tuhin Chakrabarty and Philippe Laban and Divyansh Agarwal and Smaranda Muresan and Chien-Sheng Wu},
      year={2024},
      eprint={2309.14556},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2309.14556}, 
}


@article{Guilford1967CreativityYT,
  title={Creativity: Yesterday, Today and Tomorrow},
  author={J Paul Guilford},
  journal={Journal of Creative Behavior},
  year={1967},
  volume={1},
  pages={3-14},
  url={https://api.semanticscholar.org/CorpusID:143529843}
}


@article{patterson2024audra,
  title={AuDrA: An automated drawing assessment platform for evaluating creativity},
  author={Patterson, John D and Barbot, Baptiste and Lloyd-Cox, James and Beaty, Roger E},
  journal={Behavior Research Methods},
  volume={56},
  number={4},
  pages={3619--3636},
  year={2024},
  publisher={Springer}
}

@InProceedings{Zhong_2024_CVPR,
    author    = {Zhong, Shanshan and Huang, Zhongzhan and Gao, Shanghua and Wen, Wushao and Lin, Liang and Zitnik, Marinka and Zhou, Pan},
    title     = {Let's Think Outside the Box: Exploring Leap-of-Thought in Large Language Models with Creative Humor Generation},
    booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
    month     = {June},
    year      = {2024},
    pages     = {13246-13257}
}

@article{Zhao_2025,
   title={Assessing and Understanding Creativity in Large Language Models},
   volume={22},
   ISSN={2731-5398},
   url={http://dx.doi.org/10.1007/s11633-025-1546-4},
   DOI={10.1007/s11633-025-1546-4},
   number={3},
   journal={Machine Intelligence Research},
   publisher={Springer Science and Business Media LLC},
   author={Zhao, Yunpu and Zhang, Rui and Li, Wenyi and Li, Ling},
   year={2025},
   month=apr, pages={417–436} }

@article{zar2005spearman,
  title={Spearman rank correlation},
  author={Zar, Jerrold H},
  journal={Encyclopedia of Biostatistics},
  volume={7},
  year={2005},
  publisher={Wiley Online Library}
}

@incollection{benesty2009pearson,
  title={Pearson correlation coefficient},
  author={Benesty, Jacob and Chen, Jingdong and Huang, Yiteng and Cohen, Israel},
  booktitle={Noise reduction in speech processing},
  pages={1--4},
  year={2009},
  publisher={Springer}
}

@article{bai2023qwen,
  title={Qwen technical report},
  author={Bai, Jinze and Bai, Shuai and Chu, Yunfei and Cui, Zeyu and Dang, Kai and Deng, Xiaodong and Fan, Yang and Ge, Wenbin and Han, Yu and Huang, Fei and others},
  journal={arXiv preprint arXiv:2309.16609},
  year={2023}
}

@article{hu2022lora,
  title={Lora: Low-rank adaptation of large language models.},
  author={Hu, Edward J and Shen, Yelong and Wallis, Phillip and Allen-Zhu, Zeyuan and Li, Yuanzhi and Wang, Shean and Wang, Lu and Chen, Weizhu and others},
  journal={ICLR},
  volume={1},
  number={2},
  pages={3},
  year={2022}
}

@misc{pan2025tinyrewardmodels,
      title={Tiny Reward Models}, 
      author={Sarah Pan},
      year={2025},
      eprint={2507.09973},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2507.09973}, 
}

@misc{jiang2023llmblenderensemblinglargelanguage,
      title={LLM-Blender: Ensembling Large Language Models with Pairwise Ranking and Generative Fusion}, 
      author={Dongfu Jiang and Xiang Ren and Bill Yuchen Lin},
      year={2023},
      eprint={2306.02561},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2306.02561}, 
}

@misc{sidahmed2024parameterefficientreinforcementlearning,
      title={Parameter Efficient Reinforcement Learning from Human Feedback}, 
      author={Hakim Sidahmed and Samrat Phatale and Alex Hutcheson and Zhuonan Lin and Zhang Chen and Zac Yu and Jarvis Jin and Simral Chaudhary and Roman Komarytsia and Christiane Ahlheim and Yonghao Zhu and Bowen Li and Saravanan Ganesh and Bill Byrne and Jessica Hoffmann and Hassan Mansoor and Wei Li and Abhinav Rastogi and Lucas Dixon},
      year={2024},
      eprint={2403.10704},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2403.10704}, 
}

@misc{fisch2025robustpreferenceoptimizationreward,
      title={Robust Preference Optimization through Reward Model Distillation}, 
      author={Adam Fisch and Jacob Eisenstein and Vicky Zayats and Alekh Agarwal and Ahmad Beirami and Chirag Nagpal and Pete Shaw and Jonathan Berant},
      year={2025},
      eprint={2405.19316},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2405.19316}, 
}

@misc{nath2025simultaneousrewarddistillationpreference,
      title={Simultaneous Reward Distillation and Preference Learning: Get You a Language Model Who Can Do Both}, 
      author={Abhijnan Nath and Changsoo Jung and Ethan Seefried and Nikhil Krishnaswamy},
      year={2025},
      eprint={2410.08458},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/2410.08458}, 
}

@misc{zhang2025distilldatarewardssmaller,
      title={Distill Not Only Data but Also Rewards: Can Smaller Language Models Surpass Larger Ones?}, 
      author={Yudi Zhang and Lu Wang and Meng Fang and Yali Du and Chenghua Huang and Jun Wang and Qingwei Lin and Mykola Pechenizkiy and Dongmei Zhang and Saravan Rajmohan and Qi Zhang},
      year={2025},
      eprint={2502.19557},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2502.19557}, 
}







@article{10.1109/TAMD.2010.2056368,
author = {Schmidhuber, J.},
title = {Formal Theory of Creativity, Fun, and Intrinsic Motivation},
year = {2010},
issue_date = {September 2010},
publisher = {IEEE Press},
volume = {2},
number = {3},
issn = {1943-0604},
url = {https://doi.org/10.1109/TAMD.2010.2056368},
doi = {10.1109/TAMD.2010.2056368},
abstract = {The simple, but general formal theory of fun and intrinsic motivation and creativity (1990-2010) is based on the concept of maximizing intrinsic reward for the active creation or discovery of novel, surprising patterns allowing for improved prediction or data compression. It generalizes the traditional field of active learning, and is related to old, but less formal ideas in aesthetics theory and developmental psychology. It has been argued that the theory explains many essential aspects of intelligence including autonomous development, science, art, music, and humor. This overview first describes theoretically optimal (but not necessarily practical) ways of implementing the basic computational principles on exploratory, intrinsically motivated agents or robots, encouraging them to provoke event sequences exhibiting previously unknown, but learnable algorithmic regularities. Emphasis is put on the importance of limited computational resources for online prediction and compression. Discrete and continuous time formulations are given. Previous practical, but nonoptimal implementations (1991, 1995, and 1997-2002) are reviewed, as well as several recent variants by others (2005-2010). A simplified typology addresses current confusion concerning the precise nature of intrinsic motivation.},
journal = {IEEE Trans. on Auton. Ment. Dev.},
month = sep,
pages = {230–247},
numpages = {18},
keywords = {Active learning, aesthetics theory, art, attention, developmental psychology, formal theory of creativity, fun, humor, limited computational resources, music, novel patterns, novelty, science, surprise, typology of intrinsic motivation}
}

@misc{bellemare2016unifyingcountbasedexplorationintrinsic,
      title={Unifying Count-Based Exploration and Intrinsic Motivation}, 
      author={Marc G. Bellemare and Sriram Srinivasan and Georg Ostrovski and Tom Schaul and David Saxton and Remi Munos},
      year={2016},
      eprint={1606.01868},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/1606.01868}, 
}

@misc{houthooft2017vimevariationalinformationmaximizing,
      title={VIME: Variational Information Maximizing Exploration}, 
      author={Rein Houthooft and Xi Chen and Yan Duan and John Schulman and Filip De Turck and Pieter Abbeel},
      year={2017},
      eprint={1605.09674},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/1605.09674}, 
}

@misc{pathak2017curiositydrivenexplorationselfsupervisedprediction,
      title={Curiosity-driven Exploration by Self-supervised Prediction}, 
      author={Deepak Pathak and Pulkit Agrawal and Alexei A. Efros and Trevor Darrell},
      year={2017},
      eprint={1705.05363},
      archivePrefix={arXiv},
      primaryClass={cs.LG},
      url={https://arxiv.org/abs/1705.05363}, 
}

@misc{madotto2020explorationbasedlanguagelearning,
      title={Exploration Based Language Learning for Text-Based Games}, 
      author={Andrea Madotto and Mahdi Namazifar and Joost Huizinga and Piero Molino and Adrien Ecoffet and Huaixiu Zheng and Alexandros Papangelis and Dian Yu and Chandra Khatri and Gokhan Tur},
      year={2020},
      eprint={2001.08868},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2001.08868}, 
}

@misc{wan2025enhancingpersonalizedmultiturndialogue,
      title={Enhancing Personalized Multi-Turn Dialogue with Curiosity Reward}, 
      author={Yanming Wan and Jiaxing Wu and Marwa Abdulhai and Lior Shani and Natasha Jaques},
      year={2025},
      eprint={2504.03206},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2504.03206}, 
}

@article{cohen1960coefficient,
  title={A coefficient of agreement for nominal scales},
  author={Cohen, Jacob},
  journal={Educational and psychological measurement},
  volume={20},
  number={1},
  pages={37--46},
  year={1960},
  publisher={Sage Publications Sage CA: Thousand Oaks, CA}
}

@article{panickssery2024llm,
  title={Llm evaluators recognize and favor their own generations},
  author={Panickssery, Arjun and Bowman, Samuel and Feng, Shi},
  journal={Advances in Neural Information Processing Systems},
  volume={37},
  pages={68772--68802},
  year={2024}
}

@misc{wang2019gluemultitaskbenchmarkanalysis,
      title={GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding}, 
      author={Alex Wang and Amanpreet Singh and Julian Michael and Felix Hill and Omer Levy and Samuel R. Bowman},
      year={2019},
      eprint={1804.07461},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/1804.07461}, 
}

@misc{russakovsky2015imagenetlargescalevisual,
      title={ImageNet Large Scale Visual Recognition Challenge}, 
      author={Olga Russakovsky and Jia Deng and Hao Su and Jonathan Krause and Sanjeev Satheesh and Sean Ma and Zhiheng Huang and Andrej Karpathy and Aditya Khosla and Michael Bernstein and Alexander C. Berg and Li Fei-Fei},
      year={2015},
      eprint={1409.0575},
      archivePrefix={arXiv},
      primaryClass={cs.CV},
      url={https://arxiv.org/abs/1409.0575}, 
}

@article{cobbe2021gsm8k,
  title={Training Verifiers to Solve Math Word Problems},
  author={Cobbe, Karl and Kosaraju, Vineet and Bavarian, Mohammad and Chen, Mark and Jun, Heewoo and Kaiser, Lukasz and Plappert, Matthias and Tworek, Jerry and Hilton, Jacob and Nakano, Reiichiro and Hesse, Christopher and Schulman, John},
  journal={arXiv preprint arXiv:2110.14168},
  year={2021}
}

@misc{wei2023chainofthoughtpromptingelicitsreasoning,
      title={Chain-of-Thought Prompting Elicits Reasoning in Large Language Models}, 
      author={Jason Wei and Xuezhi Wang and Dale Schuurmans and Maarten Bosma and Brian Ichter and Fei Xia and Ed Chi and Quoc Le and Denny Zhou},
      year={2023},
      eprint={2201.11903},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2201.11903}, 
}

@misc{wang2023selfconsistencyimproveschainthought,
      title={Self-Consistency Improves Chain of Thought Reasoning in Language Models}, 
      author={Xuezhi Wang and Jason Wei and Dale Schuurmans and Quoc Le and Ed Chi and Sharan Narang and Aakanksha Chowdhery and Denny Zhou},
      year={2023},
      eprint={2203.11171},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2203.11171}, 
}

@misc{wataoka2025selfpreferencebiasllmasajudge,
      title={Self-Preference Bias in LLM-as-a-Judge}, 
      author={Koki Wataoka and Tsubasa Takahashi and Ryokan Ri},
      year={2025},
      eprint={2410.21819},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2410.21819}, 
}

@book{Torrance1966TTCT,
  author    = {Torrance, E. Paul},
  title     = {Torrance Tests of Creative Thinking: Norms--Technical Manual (Research Edition)},
  address   = {Princeton, NJ},
  publisher = {Personnel Press},
  year      = {1966}
}


@article{burda2018rnd,
  author  = {Burda, Yuri and Edwards, Harrison and Storkey, Amos and Klimov, Oleg},
  title   = {Exploration by Random Network Distillation},
  journal = {arXiv preprint arXiv:1810.12894},
  year    = {2018}
}

@article{Dawid1979MaximumLE,
  title={Maximum Likelihood Estimation of Observer Error‐Rates Using the EM Algorithm},
  author={A. Philip Dawid and Allan Skene},
  journal={Journal of The Royal Statistical Society Series C-applied Statistics},
  year={1979},
  volume={28},
  pages={20-28},
  url={https://api.semanticscholar.org/CorpusID:45813168}
}

@misc{owen2013monte,
  title={Monte Carlo theory, methods and examples},
  author={Owen, Art B},
  year={2013},
  publisher={Stanford}
}

@book{agresti2013,
  author    = {Alan Agresti},
  title     = {Categorical Data Analysis},
  edition   = {3rd},
  year      = {2013},
  publisher = {John Wiley \& Sons}
}

@article{davani-etal-2022-dealing,
    title = "Dealing with Disagreements: Looking Beyond the Majority Vote in Subjective Annotations",
    author = "Mostafazadeh Davani, Aida  and
      D{\'i}az, Mark  and
      Prabhakaran, Vinodkumar",
    editor = "Roark, Brian  and
      Nenkova, Ani",
    journal = "Transactions of the Association for Computational Linguistics",
    volume = "10",
    year = "2022",
    address = "Cambridge, MA",
    publisher = "MIT Press",
    url = "https://aclanthology.org/2022.tacl-1.6/",
    doi = "10.1162/tacl_a_00449",
    pages = "92--110",
    abstract = "Majority voting and averaging are common approaches used to resolve annotator disagreements and derive single ground truth labels from multiple annotations. However, annotators may systematically disagree with one another, often reflecting their individual biases and values, especially in the case of subjective tasks such as detecting affect, aggression, and hate speech. Annotator disagreements may capture important nuances in such tasks that are often ignored while aggregating annotations to a single ground truth. In order to address this, we investigate the efficacy of multi-annotator models. In particular, our multi-task based approach treats predicting each annotators' judgements as separate subtasks, while sharing a common learned representation of the task. We show that this approach yields same or better performance than aggregating labels in the data prior to training across seven different binary classification tasks. Our approach also provides a way to estimate uncertainty in predictions, which we demonstrate better correlate with annotation disagreements than traditional methods. Being able to model uncertainty is especially useful in deployment scenarios where knowing when not to make a prediction is important."
}

@misc{vu2024foundationalautoraterstaminglarge,
      title={Foundational Autoraters: Taming Large Language Models for Better Automatic Evaluation}, 
      author={Tu Vu and Kalpesh Krishna and Salaheddin Alzubi and Chris Tar and Manaal Faruqui and Yun-Hsuan Sung},
      year={2024},
      eprint={2407.10817},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2407.10817}, 
}

@misc{panickssery2024llmevaluatorsrecognizefavor,
      title={LLM Evaluators Recognize and Favor Their Own Generations}, 
      author={Arjun Panickssery and Samuel R. Bowman and Shi Feng},
      year={2024},
      eprint={2404.13076},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2404.13076}, 
}

@inproceedings{hovy-etal-2013-learning,
    title = "Learning Whom to Trust with {MACE}",
    author = "Hovy, Dirk  and
      Berg-Kirkpatrick, Taylor  and
      Vaswani, Ashish  and
      Hovy, Eduard",
    editor = "Vanderwende, Lucy  and
      Daum{\'e} III, Hal  and
      Kirchhoff, Katrin",
    booktitle = "Proceedings of the 2013 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies",
    month = jun,
    year = "2013",
    address = "Atlanta, Georgia",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/N13-1132/",
    pages = "1120--1130"
}

@inproceedings{NIPS2009_f899139d,
 author = {Whitehill, Jacob and Wu, Ting-fan and Bergsma, Jacob and Movellan, Javier and Ruvolo, Paul},
 booktitle = {Advances in Neural Information Processing Systems},
 editor = {Y. Bengio and D. Schuurmans and J. Lafferty and C. Williams and A. Culotta},
 pages = {},
 publisher = {Curran Associates, Inc.},
 title = {Whose Vote Should Count More: Optimal Integration of Labels from Labelers of Unknown Expertise},
 url = {https://proceedings.neurips.cc/paper_files/paper/2009/file/f899139df5e1059396431415e770c6dd-Paper.pdf},
 volume = {22},
 year = {2009}
}

@misc{openai2024openaio1card,
      title={OpenAI o1 System Card}, 
      author={OpenAI and : and Aaron Jaech and Adam Kalai and Adam Lerer and Adam Richardson and Ahmed El-Kishky and Aiden Low and Alec Helyar and Aleksander Madry and Alex Beutel and Alex Carney and Alex Iftimie and Alex Karpenko and Alex Tachard Passos and Alexander Neitz and Alexander Prokofiev and Alexander Wei and Allison Tam and Ally Bennett and Ananya Kumar and Andre Saraiva and Andrea Vallone and Andrew Duberstein and Andrew Kondrich and Andrey Mishchenko and Andy Applebaum and Angela Jiang and Ashvin Nair and Barret Zoph and Behrooz Ghorbani and Ben Rossen and Benjamin Sokolowsky and Boaz Barak and Bob McGrew and Borys Minaiev and Botao Hao and Bowen Baker and Brandon Houghton and Brandon McKinzie and Brydon Eastman and Camillo Lugaresi and Cary Bassin and Cary Hudson and Chak Ming Li and Charles de Bourcy and Chelsea Voss and Chen Shen and Chong Zhang and Chris Koch and Chris Orsinger and Christopher Hesse and Claudia Fischer and Clive Chan and Dan Roberts and Daniel Kappler and Daniel Levy and Daniel Selsam and David Dohan and David Farhi and David Mely and David Robinson and Dimitris Tsipras and Doug Li and Dragos Oprica and Eben Freeman and Eddie Zhang and Edmund Wong and Elizabeth Proehl and Enoch Cheung and Eric Mitchell and Eric Wallace and Erik Ritter and Evan Mays and Fan Wang and Felipe Petroski Such and Filippo Raso and Florencia Leoni and Foivos Tsimpourlas and Francis Song and Fred von Lohmann and Freddie Sulit and Geoff Salmon and Giambattista Parascandolo and Gildas Chabot and Grace Zhao and Greg Brockman and Guillaume Leclerc and Hadi Salman and Haiming Bao and Hao Sheng and Hart Andrin and Hessam Bagherinezhad and Hongyu Ren and Hunter Lightman and Hyung Won Chung and Ian Kivlichan and Ian O'Connell and Ian Osband and Ignasi Clavera Gilaberte and Ilge Akkaya and Ilya Kostrikov and Ilya Sutskever and Irina Kofman and Jakub Pachocki and James Lennon and Jason Wei and Jean Harb and Jerry Twore and Jiacheng Feng and Jiahui Yu and Jiayi Weng and Jie Tang and Jieqi Yu and Joaquin Quiñonero Candela and Joe Palermo and Joel Parish and Johannes Heidecke and John Hallman and John Rizzo and Jonathan Gordon and Jonathan Uesato and Jonathan Ward and Joost Huizinga and Julie Wang and Kai Chen and Kai Xiao and Karan Singhal and Karina Nguyen and Karl Cobbe and Katy Shi and Kayla Wood and Kendra Rimbach and Keren Gu-Lemberg and Kevin Liu and Kevin Lu and Kevin Stone and Kevin Yu and Lama Ahmad and Lauren Yang and Leo Liu and Leon Maksin and Leyton Ho and Liam Fedus and Lilian Weng and Linden Li and Lindsay McCallum and Lindsey Held and Lorenz Kuhn and Lukas Kondraciuk and Lukasz Kaiser and Luke Metz and Madelaine Boyd and Maja Trebacz and Manas Joglekar and Mark Chen and Marko Tintor and Mason Meyer and Matt Jones and Matt Kaufer and Max Schwarzer and Meghan Shah and Mehmet Yatbaz and Melody Y. Guan and Mengyuan Xu and Mengyuan Yan and Mia Glaese and Mianna Chen and Michael Lampe and Michael Malek and Michele Wang and Michelle Fradin and Mike McClay and Mikhail Pavlov and Miles Wang and Mingxuan Wang and Mira Murati and Mo Bavarian and Mostafa Rohaninejad and Nat McAleese and Neil Chowdhury and Neil Chowdhury and Nick Ryder and Nikolas Tezak and Noam Brown and Ofir Nachum and Oleg Boiko and Oleg Murk and Olivia Watkins and Patrick Chao and Paul Ashbourne and Pavel Izmailov and Peter Zhokhov and Rachel Dias and Rahul Arora and Randall Lin and Rapha Gontijo Lopes and Raz Gaon and Reah Miyara and Reimar Leike and Renny Hwang and Rhythm Garg and Robin Brown and Roshan James and Rui Shu and Ryan Cheu and Ryan Greene and Saachi Jain and Sam Altman and Sam Toizer and Sam Toyer and Samuel Miserendino and Sandhini Agarwal and Santiago Hernandez and Sasha Baker and Scott McKinney and Scottie Yan and Shengjia Zhao and Shengli Hu and Shibani Santurkar and Shraman Ray Chaudhuri and Shuyuan Zhang and Siyuan Fu and Spencer Papay and Steph Lin and Suchir Balaji and Suvansh Sanjeev and Szymon Sidor and Tal Broda and Aidan Clark and Tao Wang and Taylor Gordon and Ted Sanders and Tejal Patwardhan and Thibault Sottiaux and Thomas Degry and Thomas Dimson and Tianhao Zheng and Timur Garipov and Tom Stasi and Trapit Bansal and Trevor Creech and Troy Peterson and Tyna Eloundou and Valerie Qi and Vineet Kosaraju and Vinnie Monaco and Vitchyr Pong and Vlad Fomenko and Weiyi Zheng and Wenda Zhou and Wes McCabe and Wojciech Zaremba and Yann Dubois and Yinghai Lu and Yining Chen and Young Cha and Yu Bai and Yuchen He and Yuchen Zhang and Yunyun Wang and Zheng Shao and Zhuohan Li},
      year={2024},
      eprint={2412.16720},
      archivePrefix={arXiv},
      primaryClass={cs.AI},
      url={https://arxiv.org/abs/2412.16720}, 
}
@misc{deepseekai2025deepseekr1incentivizingreasoningcapability,
      title={DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning}, 
      author={DeepSeek-AI and Daya Guo and Dejian Yang and Haowei Zhang and Junxiao Song and Ruoyu Zhang and Runxin Xu and Qihao Zhu and Shirong Ma and Peiyi Wang and Xiao Bi and Xiaokang Zhang and Xingkai Yu and Yu Wu and Z. F. Wu and Zhibin Gou and Zhihong Shao and Zhuoshu Li and Ziyi Gao and Aixin Liu and Bing Xue and Bingxuan Wang and Bochao Wu and Bei Feng and Chengda Lu and Chenggang Zhao and Chengqi Deng and Chenyu Zhang and Chong Ruan and Damai Dai and Deli Chen and Dongjie Ji and Erhang Li and Fangyun Lin and Fucong Dai and Fuli Luo and Guangbo Hao and Guanting Chen and Guowei Li and H. Zhang and Han Bao and Hanwei Xu and Haocheng Wang and Honghui Ding and Huajian Xin and Huazuo Gao and Hui Qu and Hui Li and Jianzhong Guo and Jiashi Li and Jiawei Wang and Jingchang Chen and Jingyang Yuan and Junjie Qiu and Junlong Li and J. L. Cai and Jiaqi Ni and Jian Liang and Jin Chen and Kai Dong and Kai Hu and Kaige Gao and Kang Guan and Kexin Huang and Kuai Yu and Lean Wang and Lecong Zhang and Liang Zhao and Litong Wang and Liyue Zhang and Lei Xu and Leyi Xia and Mingchuan Zhang and Minghua Zhang and Minghui Tang and Meng Li and Miaojun Wang and Mingming Li and Ning Tian and Panpan Huang and Peng Zhang and Qiancheng Wang and Qinyu Chen and Qiushi Du and Ruiqi Ge and Ruisong Zhang and Ruizhe Pan and Runji Wang and R. J. Chen and R. L. Jin and Ruyi Chen and Shanghao Lu and Shangyan Zhou and Shanhuang Chen and Shengfeng Ye and Shiyu Wang and Shuiping Yu and Shunfeng Zhou and Shuting Pan and S. S. Li and Shuang Zhou and Shaoqing Wu and Shengfeng Ye and Tao Yun and Tian Pei and Tianyu Sun and T. Wang and Wangding Zeng and Wanjia Zhao and Wen Liu and Wenfeng Liang and Wenjun Gao and Wenqin Yu and Wentao Zhang and W. L. Xiao and Wei An and Xiaodong Liu and Xiaohan Wang and Xiaokang Chen and Xiaotao Nie and Xin Cheng and Xin Liu and Xin Xie and Xingchao Liu and Xinyu Yang and Xinyuan Li and Xuecheng Su and Xuheng Lin and X. Q. Li and Xiangyue Jin and Xiaojin Shen and Xiaosha Chen and Xiaowen Sun and Xiaoxiang Wang and Xinnan Song and Xinyi Zhou and Xianzu Wang and Xinxia Shan and Y. K. Li and Y. Q. Wang and Y. X. Wei and Yang Zhang and Yanhong Xu and Yao Li and Yao Zhao and Yaofeng Sun and Yaohui Wang and Yi Yu and Yichao Zhang and Yifan Shi and Yiliang Xiong and Ying He and Yishi Piao and Yisong Wang and Yixuan Tan and Yiyang Ma and Yiyuan Liu and Yongqiang Guo and Yuan Ou and Yuduan Wang and Yue Gong and Yuheng Zou and Yujia He and Yunfan Xiong and Yuxiang Luo and Yuxiang You and Yuxuan Liu and Yuyang Zhou and Y. X. Zhu and Yanhong Xu and Yanping Huang and Yaohui Li and Yi Zheng and Yuchen Zhu and Yunxian Ma and Ying Tang and Yukun Zha and Yuting Yan and Z. Z. Ren and Zehui Ren and Zhangli Sha and Zhe Fu and Zhean Xu and Zhenda Xie and Zhengyan Zhang and Zhewen Hao and Zhicheng Ma and Zhigang Yan and Zhiyu Wu and Zihui Gu and Zijia Zhu and Zijun Liu and Zilin Li and Ziwei Xie and Ziyang Song and Zizheng Pan and Zhen Huang and Zhipeng Xu and Zhongyu Zhang and Zhen Zhang},
      year={2025},
      eprint={2501.12948},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2501.12948}, 
}