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cs.CL2024★ 1 cited
Hypothesis Testing Prompting Improves Deductive Reasoning in Large Language Models
Yitian Li, Jidong Tian, Hao He +1
Combining different forms of prompts with pre-trained large language models has yielded remarkable results on reasoning tasks (e.g. Chain-of-Thought prompting). However, along with…
cs.CL2024
Logical Negation Augmenting and Debiasing for Prompt-based Methods
Yitian Li, Jidong Tian, Hao He +1
Prompt-based methods have gained increasing attention on NLP and shown validity on many downstream tasks. Many works have focused on mining these methods' potential for knowledge e…
cs.CL2024★ 1 cited
Comparable Demonstrations are Important in In-Context Learning: A Novel Perspective on Demonstration Selection
Caoyun Fan, Jidong Tian, Yitian Li +2
In-Context Learning (ICL) is an important paradigm for adapting Large Language Models (LLMs) to downstream tasks through a few demonstrations. Despite the great success of ICL, the…