3 papers
cs.CL2025
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…
cs.CL2025
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…
cs.CL2025
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…