Awesome LLM Self-Consistency: A Curated List of Self-consistency in Large Language Models
This repository, called Self-Consistency of LLMs, contains a collection of resources and papers on Self-Consistency in Large Language Models.
"I can't see a path that guarantees safety. We're entering a period of great uncertainty where we're dealing with things we've never dealt with before, and we can't afford to get it wrong with these things because they might take over." - Geoffrey Hinton, Professor, Department of Computer Science, University of Toronto, October 5, 2023
Welcome to share your papers, thoughts, and ideas by submitting an issue!
Teach Language Models to Reason
Denny Zhou, Google DeepMind
[Link]
Sept 2023
Foundation Models for Natural Language Processing - Pre-trained Language Models Integrating Media
Gerhard Paaß, Sven Giesselbach
Artificial Intelligence: Foundations, Theory, and Algorithms (Springer Nature), [Link]
16 Feb 2023
GSM8K-Consistency:
Consistency of Arithmetic Reasoning on GSM8K Benchmark
Shuyue Jia
Hugging Face 2023, [Hugging Face] [GitHub]
01 Dec 2023
GSM8K:
Training Verifiers to Solve Math Word Problems
Karl Cobbe, Vineet Kosaraju, Mohammad Bavarian, Mark Chen, Heewoo Jun, Lukasz Kaiser, Matthias Plappert, Jerry Tworek, Jacob Hilton, Reiichiro Nakano, Christopher Hesse, John Schulman
arXiv 2021, [Paper] [GitHub] [Blog Post]
18 Nov 2021
SingleEq:
Parsing Algebraic Word Problems into Equations
Rik Koncel-Kedziorski, Hannaneh Hajishirzi, Ashish Sabharwal, Oren Etzioni, Siena Dumas Ang
TACL 2015, [Paper] [Gitlab]
24 June 2015
AddSub:
Learning to Solve Arithmetic Word Problems with Verb Categorization
Mohammad Javad Hosseini, Hannaneh Hajishirzi, Oren Etzioni, Nate Kushman
EMNLP 2014, [Paper] [Gitlab]
25 Oct 2014
MultiArith:
Solving General Arithmetic Word Problems
Subhro Roy, Dan Roth
EMNLP 2015, [Paper] [Webpage]
17 Sept 2015
AQUA-RAT:
Program Induction by Rationale Generation : Learning to Solve and Explain Algebraic Word Problems
Wang Ling, Dani Yogatama, Chris Dyer, Phil Blunsom
ACL 2017, [Paper] [GitHub]
30 July 2017
SVAMP:
Are NLP Models really able to Solve Simple Math Word Problems?
Arkil Patel, Satwik Bhattamishra, Navin Goyal
NAACL 2021, [Paper] [GitHub]
6 July 2021
ASDiv:
A Diverse Corpus for Evaluating and Developing English Math Word Problem Solvers
Shen-yun Miao, Chao-Chun Liang, Keh-Yih Su
ACL 2020, [Paper] [GitHub]
5 July 2020
CSQA:
CommonsenseQA: A Question Answering Challenge Targeting Commonsense Knowledge
Alon Talmor, Jonathan Herzig, Nicholas Lourie, Jonathan Berant
NAACL 2019, [Paper] [Webpage]
15 Mar 2019
BECEL:
BECEL: Benchmark for Consistency Evaluation of Language Models
Myeongjun Jang, Deuk Sin Kwon, Thomas Lukasiewicz
COLING 2022, [Paper] [GitHub]
12 Oct 2022
Paraphrased SQuAD Questions:
Improving the Robustness of Question Answering Systems to Question Paraphrasing
Wee Chung Gan, Hwee Tou Ng
ACL 2019, [Paper] [GitHub]
28 July 2019
BECEL:
BECEL: Benchmark for Consistency Evaluation of Language Models
Myeongjun Jang, Deuk Sin Kwon, Thomas Lukasiewicz
COLING 2022, [Paper] [GitHub]
12 Oct 2022
Two Failures of Self-Consistency in the Multi-Step Reasoning of LLMs
Angelica Chen, Jason Phang, Alicia Parrish, Vishakh Padmakumar, Chen Zhao, Samuel R. Bowman, Kyunghyun Cho
arXiv 2023, [Paper]
2 Oct 2023
mParaRel:
mParaRel: Factual Consistency of Multilingual Pretrained Language Models
Constanza Fierro, Anders Søgaard
Findings of ACL: ACL 2022, [Paper] [GitHub]
22 Mar 2022
ParaRel:
ParaRel:metal:: Measuring and Improving Consistency in Pretrained Language Models
Yanai Elazar, Nora Kassner, Shauli Ravfogel, Abhilasha Ravichander, Eduard Hovy, Hinrich Schütze, Yoav Goldberg
TACL 2021, [Paper] [GitHub] [Presentation]
29 May 2021
Math-Shepherd: Verify and Reinforce LLMs Step-by-step without Human Annotations
Peiyi Wang, Lei Li, Zhihong Shao, R.X. Xu, Damai Dai, Yifei Li, Deli Chen, Y.Wu, Zhifang Sui
arXiv 2023, [Paper]
28 Dec 2023
A Survey of Reasoning with Foundation Models
Jiankai Sun, Chuanyang Zheng, Enze Xie, Zhengying Liu, Ruihang Chu, Jianing Qiu, Jiaqi Xu, Mingyu Ding, Hongyang Li, Mengzhe Geng, Yue Wu, Wenhai Wang, Junsong Chen, Zhangyue Yin, Xiaozhe Ren, Jie Fu, Junxian He, Wu Yuan, Qi Liu, Xihui Liu, Yu Li, Hao Dong, Yu Cheng, Ming Zhang, Pheng Ann Heng, Jifeng Dai, Ping Luo, Jingdong Wang, Ji-Rong Wen, Xipeng Qiu, Yike Guo, Hui Xiong, Qun Liu, Zhenguo Li
arXiv 2023, [Paper] [GitHub]
26 Dec 2023
Query and Response Augmentation Cannot Help Out-of-domain Math Reasoning Generalization
Chengpeng Li, Zheng Yuan, Hongyi Yuan, Guanting Dong, Keming Lu, Jiancan Wu, Chuanqi Tan, Xiang Wang, Chang Zhou
arXiv 2023, [Paper] [GitHub]
1 Nov 2023
MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models
Longhui Yu, Weisen Jiang, Han Shi, Jincheng Yu, Zhengying Liu, Yu Zhang, James T. Kwok, Zhenguo Li, Adrian Weller, Weiyang Liu
arXiv 2023, [Paper] [GitHub]
9 Oct 2023
Large Language Models are Better Reasoners with Self-Verification
Yixuan Weng, Minjun Zhu, Fei Xia, Bin Li, Shizhu He, Shengping Liu, Bin Sun, Kang Liu, Jun Zhao
EMNLP 2023 Findings, [Paper] [GitHub]
19 Oct 2023
Reasoning with Language Model Prompting: A Survey
Shuofei Qiao, Yixin Ou, Ningyu Zhang, Xiang Chen, Yunzhi Yao, Shumin Deng, Chuanqi Tan, Fei Huang, Huajun Chen
ACL 2023, [Paper] [GitHub]
18 Sep 2023
Scaling Relationship on Learning Mathematical Reasoning with Large Language Models
Zheng Yuan, Hongyi Yuan, Chengpeng Li, Guanting Dong, Keming Lu, Chuanqi Tan, Chang Zhou, Jingren Zhou
arXiv 2023, [Paper] [GitHub]
3 Aug 2023
Large Language Models Can Be Easily Distracted by Irrelevant Context
Freda Shi, Xinyun Chen, Kanishka Misra, Nathan Scales, David Dohan, Ed Chi, Nathanael Schärli, Denny Zhou
ICML 2023, [Paper] [GitHub]
6 Jun 2023
Towards Reasoning in Large Language Models: A Survey
Jie Huang, Kevin Chen-Chuan Chang
Findings of ACL 2023, [Paper] [GitHub]
26 May 2023
Self-Refine: Iterative Refinement with Self-Feedback
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, Peter Clark
arXiv 2023, [Paper] [GitHub] [Webpage]
25 May 2023
Self-Refine: Iterative Refinement with Self-Feedback
Aman Madaan, Niket Tandon, Prakhar Gupta, Skyler Hallinan, Luyu Gao, Sarah Wiegreffe, Uri Alon, Nouha Dziri, Shrimai Prabhumoye, Yiming Yang, Shashank Gupta, Bodhisattwa Prasad Majumder, Katherine Hermann, Sean Welleck, Amir Yazdanbakhsh, Peter Clark
arXiv 2023, [Paper] [Website] [GitHub] [Demo]
25 May 2023
Let's Sample Step by Step: Adaptive-Consistency for Efficient Reasoning with LLMs
Pranjal Aggarwal, Aman Madaan, Yiming Yang, Mausam
arXiv 2023, [Paper] [Website] [GitHub]
19 May 2023
Self-Consistency Improves Chain of Thought Reasoning in Language Models
Xuezhi Wang, Jason Wei, Dale Schuurmans, Quoc Le, Ed Chi, Sharan Narang, Aakanksha Chowdhery, Denny Zhou
ICLR 2023, [Paper]
7 Mar 2023
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Brian Ichter, Fei Xia, Ed Chi, Quoc Le, Denny Zhou
NeurIPS 2022, [Paper]
28 Jan 2022
Semantic Consistency for Assuring Reliability of Large Language Models
Harsh Raj, Vipul Gupta, Domenic Rosati, Subhabrata Majumdar
arXiv 2023, [Paper]
17 Aug 2023
Measuring Reliability of Large Language Models through Semantic Consistency
Harsh Raj, Domenic Rosati, Subhabrata Majumdar
ML Safety Workshop, NeurIPS 2022, [Paper]
28 Nov 2022
Prompt Consistency for Zero-Shot Task Generalization
Chunting Zhou, Junxian He, Xuezhe Ma, Taylor Berg-Kirkpatrick, Graham Neubig
Findings of ACL: EMNLP 2022, [Paper] [GitHub]
27 Dec 2022
Accurate, Yet Inconsistent? Consistency Analysis on Language Understanding Models
Myeongjun Jang, Deuk Sin Kwon, Thomas Lukasiewicz
arXiv 2021, [Paper]
15 Aug 2021
Evolution of Semantic Similarity—A Survey
Dhivya Chandrasekaran, Vijay Mago
ACM Computing Survey 2021, [Paper]
30 Jan 2021
Enhancing Self-Consistency and Performance of Pre-Trained Language Models through Natural Language Inference
Eric Mitchell, Joseph Noh, Siyan Li, Will Armstrong, Ananth Agarwal, Patrick Liu, Chelsea Finn, Christopher Manning
EMNLP 2022, [Paper] [Website] [GitHub]
21 Nov 2022
RCOT: Detecting and Rectifying Factual Inconsistency in Reasoning by Reversing Chain-of-Thought
Tianci Xue, Ziqi Wang, Zhenhailong Wang, Chi Han, Pengfei Yu, Heng Ji
arXiv 2023, [Paper]
2 Oct 2023
P-Adapters: Robustly Extracting Factual Information from Language Models with Diverse Prompts
Benjamin Newman, Prafulla Kumar Choubey, Nazneen Rajani
ICLR 2022, [Paper] [GitHub]
19 Apr 2022
How Can We Know What Language Models Know?
Zhengbao Jiang, Frank F. Xu, Jun Araki, Graham Neubig
TACL 2020, [Paper] [GitHub]
3 May 2020
BiomedGPT: A Unified and Generalist Biomedical Generative Pre-trained Transformer for Vision, Language, and Multimodal Tasks
Kai Zhang, Jun Yu, Eashan Adhikarla, Rong Zhou, Zhiling Yan, Yixin Liu, Zhengliang Liu, Lifang He, Brian Davison, Xiang Li, Hui Ren, Sunyang Fu, James Zou, Wei Liu, Jing Huang, Chen Chen, Yuyin Zhou, Tianming Liu, Xun Chen, Yong Chen, Quanzheng Li, Hongfang Liu, Lichao Sun
arXiv 2024, [Paper] [GitHub]
9 Jan 2024
Can Large Language Models Reason about Medical Questions?
Valentin Liévin, Christoffer Egeberg Hother, Andreas Geert Motzfeldt, Ole Winther
arXiv 2023, [Paper] [GitHub]
24 Dec 2023
Towards Generalist Biomedical AI
Tao Tu, Shekoofeh Azizi, Danny Driess, Mike Schaekermann, Mohamed Amin, Pi-Chuan Chang, Andrew Carroll, Chuck Lau, Ryutaro Tanno, Ira Ktena, Basil Mustafa, Aakanksha Chowdhery, Yun Liu, Simon Kornblith, David Fleet, Philip Mansfield, Sushant Prakash, Renee Wong, Sunny Virmani, Christopher Semturs, S Sara Mahdavi, Bradley Green, Ewa Dominowska, Blaise Aguera y Arcas, Joelle Barral, Dale Webster, Greg S. Corrado, Yossi Matias, Karan Singhal, Pete Florence, Alan Karthikesalingam, Vivek Natarajan
arXiv 2023, [Paper] [GitHub]
26 Jul 2023
LLaVA-Med: Training a Large Language-and-Vision Assistant for Biomedicine in One Day
Chunyuan Li, Cliff Wong, Sheng Zhang, Naoto Usuyama, Haotian Liu, Jianwei Yang, Tristan Naumann, Hoifung Poon, Jianfeng Gao
arXiv 2023, [Paper] [GitHub]
1 Jun 2023
Towards Expert-Level Medical Question Answering with Large Language Models
Karan Singhal, Tao Tu, Juraj Gottweis, Rory Sayres, Ellery Wulczyn, Le Hou, Kevin Clark, Stephen Pfohl, Heather Cole-Lewis, Darlene Neal, Mike Schaekermann, Amy Wang, Mohamed Amin, Sami Lachgar, Philip Mansfield, Sushant Prakash, Bradley Green, Ewa Dominowska, Blaise Aguera y Arcas, Nenad Tomasev, Yun Liu, Renee Wong, Christopher Semturs, S. Sara Mahdavi, Joelle Barral, Dale Webster, Greg S. Corrado, Yossi Matias, Shekoofeh Azizi, Alan Karthikesalingam, Vivek Natarajan
arXiv 2023, [Paper]
16 May 2023
Large Language Models Encode Clinical Knowledge
Karan Singhal, Shekoofeh Azizi, Tao Tu, S. Sara Mahdavi, Jason Wei, Hyung Won Chung, Nathan Scales, Ajay Tanwani, Heather Cole-Lewis, Stephen Pfohl, Perry Payne, Martin Seneviratne, Paul Gamble, Chris Kelly, Nathaneal Scharli, Aakanksha Chowdhery, Philip Mansfield, Blaise Aguera y Arcas, Dale Webster, Greg S. Corrado, Yossi Matias, Katherine Chou, Juraj Gottweis, Nenad Tomasev, Yun Liu, Alvin Rajkomar, Joelle Barral, Christopher Semturs, Alan Karthikesalingam, Vivek Natarajan
Nature, [Paper]
26 Dec 2022
Multimodal Foundation Models: From Specialists to General-Purpose Assistants
Chunyuan Li, Zhe Gan, Zhengyuan Yang, Jianwei Yang, Linjie Li, Lijuan Wang, Jianfeng Gao
arXiv 2023, [Paper] [Webpage]
18 Sep 2023