Understanding the Effect of Noise in LLM Training Data with Algorithmic Chains of Thought

6 February 2024

Papers citing "Understanding the Effect of Noise in LLM Training Data with Algorithmic Chains of Thought"

6 / 6 papers shown

Title
Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes Lokesh Nagalapatti Chun-Liang Li Chih-Kuan Yeh Hootan Nakhost Yasuhisa Fujii Alexander Ratner Ranjay Krishna Chen-Yu Lee Tomas Pfister ALM 204 498 0 03 May 2023
Text and Patterns: For Effective Chain of Thought, It Takes Two to Tango Aman Madaan Amir Yazdanbakhsh LRM 136 115 0 16 Sep 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
Chain-of-Thought Prompting Elicits Reasoning in Large Language Models Jason W. Wei Xuezhi Wang Dale Schuurmans Maarten Bosma Brian Ichter F. Xia Ed H. Chi Quoc Le Denny Zhou LM&Ro LRM AI4CE ReLM 315 8,261 0 28 Jan 2022
Reasoning Like Program Executors Xinyu Pi Qian Liu Bei Chen Morteza Ziyadi Zeqi Lin Qiang Fu Yan Gao Jian-Guang Lou Weizhu Chen ReLM LRM 246 52 0 27 Jan 2022
Beyond Class-Conditional Assumption: A Primary Attempt to Combat Instance-Dependent Label Noise Pengfei Chen Junjie Ye Guangyong Chen Jingwei Zhao Pheng-Ann Heng NoLa 24 55 0 10 Dec 2020