4 papers · 1 filter
Commonsense Knowledge Editing Based on Free-Text in LLMs
Xiusheng Huang, Yequan Wang, Jun Zhao +1
Knowledge editing technology is crucial for maintaining the accuracy and timeliness of large language models (LLMs) . However, the setting of this task overlooks a significant port…
Reasons and Solutions for the Decline in Model Performance after Editing
Xiusheng Huang, Jiaxiang Liu, Yequan Wang +1
Knowledge editing technology has received widespread attention for low-cost updates of incorrect or outdated knowledge in large-scale language models. However, recent research has…
Improving Zero-shot LLM Re-Ranker with Risk Minimization
Xiaowei Yuan, Zhao Yang, Yequan Wang +2
In the Retrieval-Augmented Generation (RAG) system, advanced Large Language Models (LLMs) have emerged as effective Query Likelihood Models (QLMs) in an unsupervised way, which re-…
Discerning and Resolving Knowledge Conflicts through Adaptive Decoding with Contextual Information-Entropy Constraint
Xiaowei Yuan, Zhao Yang, Yequan Wang +3
Large language models internalize enormous parametric knowledge during pre-training. Concurrently, realistic applications necessitate external contextual knowledge to aid models on…