Large Language Models Can Self-Correct with Minimal Effort

23 May 2024

Papers citing "Large Language Models Can Self-Correct with Minimal Effort"

7 / 7 papers shown

Title
Can Large Language Models Detect Errors in Long Chain-of-Thought Reasoning? Yancheng He Shilong Li J. Liu Weixun Wang Xingyuan Bu ... Zhongyuan Peng Z. Zhang Zhicheng Zheng Wenbo Su Bo Zheng ELM LRM 79 6 0 26 Feb 2025
Instructing Large Language Models to Identify and Ignore Irrelevant Conditions Zhenyu Wu Chao Shen Meng-Long Jiang LRM 28 4 0 19 Mar 2024
Self-prompted Chain-of-Thought on Large Language Models for Open-domain Multi-hop Reasoning Jinyuan Wang Junlong Li Hai Zhao LRM ReLM 37 20 0 20 Oct 2023
Generate rather than Retrieve: Large Language Models are Strong Context Generators W. Yu Dan Iter Shuohang Wang Yichong Xu Mingxuan Ju Soumya Sanyal Chenguang Zhu Michael Zeng Meng-Long Jiang RALM AIMat 215 318 0 21 Sep 2022
Large Language Models are Zero-Shot Reasoners Takeshi Kojima S. Gu Machel Reid Yutaka Matsuo Yusuke Iwasawa ReLM LRM 291 4,048 0 24 May 2022
Self-Consistency Improves Chain of Thought Reasoning in Language Models Xuezhi Wang Jason W. Wei Dale Schuurmans Quoc Le Ed H. Chi Sharan Narang Aakanksha Chowdhery Denny Zhou ReLM BDL LRM AI4CE 297 3,163 0 21 Mar 2022
Retrieving and Reading: A Comprehensive Survey on Open-domain Question Answering Fengbin Zhu Wenqiang Lei Chao Wang Jianming Zheng Soujanya Poria Tat-Seng Chua RALM 204 251 0 04 Jan 2021