Pride and Prejudice: LLM Amplifies Self-Bias in Self-Refinement

A characteristic measure of asymmetry and its application for testing diagonal symmetry

Gabor Szekely and Tamás Móri. 2006 · 2006

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Bias correction of gcm precipitation by quantile mapping: How well do methods preserve changes in quantiles and extremes?

Alex J. Cannon, Stephen R. Sobie, and Trevor Q. Murdock. 2015 · 2015

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CommonGen: A constrained text generation challenge for generative commonsense reasoning

Bill Yuchen Lin, Wangchunshu Zhou, Ming Shen, Pei Zhou, Chandra Bhagavatula, Yejin Choi, and Xiang Ren. 2020 · 2020

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Bleurt: Learning robust metrics for text generation

Thibault Sellam, Dipanjan Das, and Ankur P Parikh. 2020 · 2020

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Experts, errors, and context: A large-scale study of human evaluation for machine translation

Markus Freitag, George Foster, David Grangier, Viresh Ratnakar, Qijun Tan, and Wolfgang Macherey. 2021 · 2021

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Measuring mathematical problem solving with the math dataset

Dan Hendrycks, Collin Burns, Saurav Kadavath, Akul Arora, Steven Basart, Eric Tang, Dawn Song, and Jacob Steinhardt. 2021 · 2021

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Learning compact metrics for mt

Amy Pu, Hyung Won Chung, Ankur P Parikh, Sebastian Gehrmann, and Thibault Sellam. 2021 · 2021

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No language left behind: Scaling human-centered machine translation

Original

Marta R Costa-jussà, James Cross, Onur Çelebi, Maha Elbayad, Kenneth Heafield, Kevin Heffernan, Elahe Kalbassi, Janice Lam, Daniel Licht, Jean Maillard, et al. 2022 · 2022

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On the limitations of reference-free evaluations of generated text

Daniel Deutsch, Rotem Dror, and Dan Roth. 2022 · 2022

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Results of WMT22 metrics shared task: Stop using BLEU – neural metrics are better and more robust

Markus Freitag, Ricardo Rei, Nitika Mathur, Chi-kiu Lo, Craig Stewart, Eleftherios Avramidis, Tom Kocmi, George Foster, Alon Lavie, and André F. T. Martins. 2022 · 2022

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Gpt-4 technical report

Original

Josh Achiam, Steven Adler, Sandhini Agarwal, Lama Ahmad, Ilge Akkaya, Florencia Leoni Aleman, Diogo Almeida, Janko Altenschmidt, Sam Altman, Shyamal Anadkat, et al. 2023 · 2023

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Speak, memory: An archaeology of books known to ChatGPT/GPT-4

Kent Chang, Mackenzie Cramer, Sandeep Soni, and David Bamman. 2023 · 2023

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Gptscore: Evaluate as you desire

Original

Jinlan Fu, See-Kiong Ng, Zhengbao Jiang, and Pengfei Liu. 2023 · 2023

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Reinforced self-training (rest) for language modeling

Original

Caglar Gulcehre, Tom Le Paine, Srivatsan Srinivasan, Ksenia Konyushkova, Lotte Weerts, Abhishek Sharma, Aditya Siddhant, Alex Ahern, Miaosen Wang, Chenjie Gu, Wolfgang Macherey, Arnaud Doucet, Orhan Firat, and Nando de Freitas. 2023 · 2023

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A closer look at the self-verification abilities of large language models in logical reasoning

Original

Ruixin Hong, Hongming Zhang, Xinyu Pang, Dong Yu, and Changshui Zhang. 2023 · 2023

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Large language models can self-improve

Jiaxin Huang, Shixiang Gu, Le Hou, Yuexin Wu, Xuezhi Wang, Hongkun Yu, and Jiawei Han. 2023a · 2023

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Critiquellm: Scaling llm-as-critic for effective and explainable evaluation of large language model generation

Original

Pei Ke, Bosi Wen, Zhuoer Feng, Xiao Liu, Xuanyu Lei, Jiale Cheng, Shengyuan Wang, Aohan Zeng, Yuxiao Dong, Hongning Wang, Jie Tang, and Minlie Huang. 2023 · 2023

Cited alongside, same era.

Findings of the 2023 conference on machine translation (WMT23): LLMs are here but not quite there yet

Tom Kocmi, Eleftherios Avramidis, Rachel Bawden, Ondřej Bojar, Anton Dvorkovich, Christian Federmann, Mark Fishel, Markus Freitag, Thamme Gowda, Roman Grundkiewicz, Barry Haddow, Philipp Koehn, Benjamin Marie, Christof Monz, Makoto Morishita, Kenton Murray, Makoto Nagata, Toshiaki Nakazawa, Martin Popel, Maja Popović, and Mariya Shmatova. 2023 · 2023

Cited alongside, same era.

Llms cannot find reasoning errors, but can correct them!

Original

Gladys Tyen, Hassan Mansoor, Peter Chen, Tony Mak, and Victor Carbune. 2023 · 2023

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Can large language models really improve by self-critiquing their own plans?

Original

Karthik Valmeekam, Matthew Marquez, and Subbarao Kambhampati. 2023 · 2023

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Self-consistency improves chain of thought reasoning in language models

Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc V Le, Ed H. Chi, Sharan Narang, Aakanksha Chowdhery, and Denny Zhou. 2023 · 2023

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INSTRUCTSCORE: Towards explainable text generation evaluation with automatic feedback

Wenda Xu, Danqing Wang, Liangming Pan, Zhenqiao Song, Markus Freitag, William Wang, and Lei Li. 2023 · 2023

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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, Hao Zhang, Joseph E. Gonzalez, and Ion Stoica. 2023 · 2023