Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning

Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning

14 December 2023

Li Lyna Zhang

Kwang-Ting Cheng

Fan Yang

Papers citing "Fewer is More: Boosting LLM Reasoning with Reinforced Context Pruning"

7 / 7 papers shown

Title
Mobile Edge Intelligence for Large Language Models: A Contemporary Survey Guanqiao Qu Qiyuan Chen Wei Wei Zheng Lin Xianhao Chen Kaibin Huang 27 37 0 09 Jul 2024
Merge, Ensemble, and Cooperate! A Survey on Collaborative Strategies in the Era of Large Language Models Jinliang Lu Ziliang Pang Min Xiao Yaochen Zhu Rui Xia Jiajun Zhang MoMe 19 17 0 08 Jul 2024
Large Language Models are Zero-Shot Reasoners Takeshi Kojima S. Gu Machel Reid Yutaka Matsuo Yusuke Iwasawa ReLM LRM 291 2,712 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
Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity Yao Lu Max Bartolo Alastair Moore Sebastian Riedel Pontus Stenetorp AILaw LRM 274 882 0 18 Apr 2021
What Makes Good In-Context Examples for GPT- $3$ ? Jiachang Liu Dinghan Shen Yizhe Zhang Bill Dolan Lawrence Carin Weizhu Chen AAML RALM 275 1,296 0 17 Jan 2021
Making Pre-trained Language Models Better Few-shot Learners Tianyu Gao Adam Fisch Danqi Chen 238 1,898 0 31 Dec 2020