5 papers
COMPKE: Complex Question Answering under Knowledge Editing
Keyuan Cheng, Zijian Kan, Zhixian He +5
Knowledge Editing, which efficiently modifies the knowledge in large language models, has gathered great attention. Current benchmarks primarily use multi-hop question answering to…
CODEMENV: Benchmarking Large Language Models on Code Migration
Keyuan Cheng, Xudong Shen, Yihao Yang +6
Large language models (LLMs) have shown remarkable capabilities across various software engineering tasks; however, their effectiveness in code migration, adapting code to run in d…
Locate-then-edit for Multi-hop Factual Recall under Knowledge Editing
Zhuoran Zhang, Yongxiang Li, Zijian Kan +3
The locate-then-edit paradigm has shown significant promise for knowledge editing (KE) in Large Language Models (LLMs). While previous methods perform well on single-hop fact recal…
Prompt-SAW: Leveraging Relation-Aware Graphs for Textual Prompt Compression
Muhammad Asif Ali, Zhengping Li, Shu Yang +8
Large Language Models (LLMs) have shown exceptional abilities for multiple different natural language processing tasks. While prompting is a crucial tool for LLM inference, we obse…
Understanding Reasoning in Chain-of-Thought from the Hopfieldian View
Lijie Hu, Liang Liu, Shu Yang +5
Large Language Models have demonstrated remarkable abilities across various tasks, with Chain-of-Thought (CoT) prompting emerging as a key technique to enhance reasoning capabiliti…