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LLM-as-a-Judge and reward models are widely used alternatives of multiple-choice questions or human annotators for large language model (LLM) evaluation.
Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu · 2002
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin · 2004
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Measuring massive multitask language understanding
Dan Hendrycks, Collin Burns, Steven Basart, Andy Zou, Mantas Mazeika, Dawn Song, and Jacob Steinhardt · 2020
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Training a helpful and harmless assistant with reinforcement learning from human feedback
Yuntao Bai, Andy Jones, Kamal Ndousse, Amanda Askell, Anna Chen, Nova DasSarma, Dawn Drain, Stanislav Fort, Deep Ganguli, Tom Henighan, et al · 2022
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Kobest: Korean balanced evaluation of significant tasks
Dohyeong Kim, Myeongjun Jang, Deuk Sin Kwon, and Eric Davis · 2022
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Cross-task generalization via natural language crowdsourcing instructions
Swaroop Mishra, Daniel Khashabi, Chitta Baral, and Hannaneh Hajishirzi · 2022
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Introducing chatgpt
OpenAI · 2022
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Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, et al · 2022
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React: Synergizing reasoning and acting in language models
Shunyu Yao, Jeffrey Zhao, Dian Yu, Nan Du, Izhak Shafran, Karthik Narasimhan, and Yuan Cao · 2022
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Rest meets react: Self-improvement for multi-step reasoning llm agent
Renat Aksitov, Sobhan Miryoosefi, Zonglin Li, Daliang Li, Sheila Babayan, Kavya Kopparapu, Zachary Fisher, Ruiqi Guo, Sushant Prakash, Pranesh Srinivasan, et al · 2023
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Revealing the structure of language model capabilities
Ryan Burnell, Han Hao, Andrew RA Conway, and Jose Hernandez Orallo · 2023
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John Joon Young Chung, Ece Kamar, and Saleema Amershi · 2023
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Raft: Reward ranked finetuning for generative foundation model alignment
Hanze Dong, Wei Xiong, Deepanshu Goyal, Yihan Zhang, Winnie Chow, Rui Pan, Shizhe Diao, Jipeng Zhang, Kashun Shum, and Tong Zhang · 2023
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Lei Huang, Weijiang Yu, Weitao Ma, Weihong Zhong, Zhangyin Feng, Haotian Wang, Qianglong Chen, Weihua Peng, Xiaocheng Feng, Bing Qin, et al · 2023
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Unveiling the general intelligence factor in language models: A psychometric approach
David Ilić · 2023
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Pretraining language models with human preferences
Tomasz Korbak, Kejian Shi, Angelica Chen, Rasika Vinayak Bhalerao, Christopher Buckley, Jason Phang, Samuel R Bowman, and Ethan Perez · 2023
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Rlaif: Scaling reinforcement learning from human feedback with ai feedback
Harrison Lee, Samrat Phatale, Hassan Mansoor, Thomas Mesnard, Johan Ferret, Kellie Lu, Colton Bishop, Ethan Hall, Victor Carbune, Abhinav Rastogi, et al · 2023
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Minzhi Li, Taiwei Shi, Caleb Ziems, Min-Yen Kan, Nancy F Chen, Zhengyuan Liu, and Diyi Yang · 2023
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G-eval: Nlg evaluation using gpt-4 with better human alignment
Yang Liu, Dan Iter, Yichong Xu, Shuohang Wang, Ruochen Xu, and Chenguang Zhu · 2023
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FActScore: Fine-grained atomic evaluation of factual precision in long form text generation
Sewon Min, Kalpesh Krishna, Xinxi Lyu, Mike Lewis, Wen-tau Yih, Pang Koh, Mohit Iyyer, Luke Zettlemoyer, and Hannaneh Hajishirzi · 2023
Cited alongside, same era.
Nash learning from human feedback
Rémi Munos, Michal Valko, Daniele Calandriello, Mohammad Gheshlaghi Azar, Mark Rowland, Zhaohan Daniel Guo, Yunhao Tang, Matthieu Geist, Thomas Mesnard, Andrea Michi, et al · 2023
Cited alongside, same era.
Gpqa: A graduate-level google-proof q&a benchmark
David Rein, Betty Li Hou, Asa Cooper Stickland, Jackson Petty, Richard Yuanzhe Pang, Julien Dirani, Julian Michael, and Samuel R Bowman · 2023
Cited alongside, same era.
Hae-rae bench: Evaluation of korean knowledge in language models
Guijin Son, Hanwool Lee, Suwan Kim, Jaecheol Lee, Je Won Yeom, Jihyu Jung, Jung Woo Kim, and Songseong Kim · 2023
Cited alongside, same era.
Cheaper, better, faster, stronger. continuing to push the frontier of ai and making it accessible to all
Mistral · 2024
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Mistral large 2407, 2024
Mistral AI · 2024
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Hello gpt-4o, 2024
OpenAI · 2024
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Introducing openai o1
OpenAI · 2024
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Logickor, 2024
Jeonghwan Park · 2024
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Offsetbias: Leveraging debiased data for tuning evaluators
Junsoo Park, Seungyeon Jwa, Meiying Ren, Daeyoung Kim, and Sanghyuk Choi · 2024
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The fineweb datasets: Decanting the web for the finest text data at scale
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Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al · 2023
Cited alongside, same era.
Flask: Fine-grained language model evaluation based on alignment skill sets
Seonghyeon Ye, Doyoung Kim, Sungdong Kim, Hyeonbin Hwang, Seungone Kim, Yongrae Jo, James Thorne, Juho Kim, and Minjoon Seo · 2023
Cited alongside, same era.
Evaluating large language models at evaluating instruction following
Zhiyuan Zeng, Jiatong Yu, Tianyu Gao, Yu Meng, Tanya Goyal, and Danqi Chen · 2023
Cited alongside, same era.
Claude 3.5 sonnet, 2024
Anthropic · 2024
Cited alongside, same era.
Aya 23: Open weight releases to further multilingual progress
Viraat Aryabumi, John Dang, Dwarak Talupuru, Saurabh Dash, David Cairuz, Hangyu Lin, Bharat Venkitesh, Madeline Smith, Kelly Marchisio, Sebastian Ruder, et al · 2024
Cited alongside, same era.
Humans or llms as the judge? a study on judgement biases
Guiming Hardy Chen, Shunian Chen, Ziche Liu, Feng Jiang, and Benyou Wang · 2024
Cited alongside, same era.
Chatbot arena: An open platform for evaluating llms by human preference
Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Hao Zhang, Banghua Zhu, Michael Jordan, Joseph E Gonzalez, et al · 2024
Cited alongside, same era.
Introducing command r+: A scalable llm built for business
Cohere · 2024
Cited alongside, same era.
Guilherme Penedo, Hynek Kydlíček, Anton Lozhkov, Margaret Mitchell, Colin Raffel, Leandro Von Werra, Thomas Wolf, et al · 2024
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Exaone 3.0 7.8 b instruction tuned language model
LG Research, Soyoung An, Kyunghoon Bae, Eunbi Choi, Stanley Jungkyu Choi, Yemuk Choi, Seokhee Hong, Yeonjung Hong, Junwon Hwang, Hyojin Jeon, et al · 2024
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Komt-bench
LG AI Research · 2024
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Kmmlu: Measuring massive multitask language understanding in korean
Guijin Son, Hanwool Lee, Sungdong Kim, Seungone Kim, Niklas Muennighoff, Taekyoon Choi, Cheonbok Park, Kang Min Yoo, and Stella Biderman · 2024
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A minimaximalist approach to reinforcement learning from human feedback
Gokul Swamy, Christoph Dann, Rahul Kidambi, Zhiwei Steven Wu, and Alekh Agarwal · 2024
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Replacing judges with juries: Evaluating llm generations with a panel of diverse models
Pat Verga, Sebastian Hofstatter, Sophia Althammer, Yixuan Su, Aleksandra Piktus, Arkady Arkhangorodsky, Minjie Xu, Naomi White, and Patrick Lewis · 2024
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Foundational autoraters: Taming large language models for better automatic evaluation
Tu Vu, Kalpesh Krishna, Salaheddin Alzubi, Chris Tar, Manaal Faruqui, and Yun-Hsuan Sung · 2024
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Reuse your rewards: Reward model transfer for zero-shot cross-lingual alignment
Zhaofeng Wu, Ananth Balashankar, Yoon Kim, Jacob Eisenstein, and Ahmad Beirami · 2024
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Iterative preference learning from human feedback: Bridging theory and practice for rlhf under kl-constraint, 2024
Wei Xiong, Hanze Dong, Chenlu Ye, Ziqi Wang, Han Zhong, Heng Ji, Nan Jiang, and Tong Zhang · 2024
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An Yang, Baosong Yang, Binyuan Hui, Bo Zheng, Bowen Yu, Chang Zhou, Chengpeng Li, Chengyuan Li, Dayiheng Liu, Fei Huang, et al · 2024
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Kang Min Yoo, Jaegeun Han, Sookyo In, Heewon Jeon, Jisu Jeong, Jaewook Kang, Hyunwook Kim, Kyung-Min Kim, Munhyong Kim, Sungju Kim, et al · 2024
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Generative verifiers: Reward modeling as next-token prediction
Lunjun Zhang, Arian Hosseini, Hritik Bansal, Mehran Kazemi, Aviral Kumar, and Rishabh Agarwal · 2024
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Judging llm-as-a-judge with mt-bench and chatbot arena
Lianmin Zheng, Wei-Lin Chiang, Ying Sheng, Siyuan Zhuang, Zhanghao Wu, Yonghao Zhuang, Zi Lin, Zhuohan Li, Dacheng Li, Eric Xing, et al · 2024
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