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Is Fine-Tuning an Effective Solution? Reassessing Knowledge Editing for Unstructured Data
Hao Xiong, Chuanyuan Tan, Wenliang Chen
Unstructured Knowledge Editing (UKE) is crucial for updating the relevant knowledge of large language models (LLMs). It focuses on unstructured inputs, such as long or free-form te…
UAQFact: Evaluating Factual Knowledge Utilization of LLMs on Unanswerable Questions
Chuanyuan Tan, Wenbiao Shao, Hao Xiong +4
Handling unanswerable questions (UAQ) is crucial for LLMs, as it helps prevent misleading responses in complex situations. While previous studies have built several datasets to ass…
Feature Extraction and Steering for Enhanced Chain-of-Thought Reasoning in Language Models
Zihao Li, Xu Wang, Yuzhe Yang +3
Large Language Models (LLMs) demonstrate the ability to solve reasoning and mathematical problems using the Chain-of-Thought (CoT) technique. Expanding CoT length, as seen in model…
NesTools: A Dataset for Evaluating Nested Tool Learning Abilities of Large Language Models
Han Han, Tong Zhu, Xiang Zhang +3
Large language models (LLMs) combined with tool learning have gained impressive results in real-world applications. During tool learning, LLMs may call multiple tools in nested ord…