3 citations · 4 across the 8 of their papers we have counts for
4 papers · 1 filter
LINKED: Eliciting, Filtering and Integrating Knowledge in Large Language Model for Commonsense Reasoning
Jiachun Li, Pengfei Cao, Chenhao Wang +6
Large language models (LLMs) sometimes demonstrate poor performance on knowledge-intensive tasks, commonsense reasoning is one of them. Researchers typically address these issues b…
RWKU: Benchmarking Real-World Knowledge Unlearning for Large Language Models
Zhuoran Jin, Pengfei Cao, Chenhao Wang +6
Large language models (LLMs) inevitably memorize sensitive, copyrighted, and harmful knowledge from the training corpus; therefore, it is crucial to erase this knowledge from the m…
AgentsCourt: Building Judicial Decision-Making Agents with Court Debate Simulation and Legal Knowledge Augmentation
Zhitao He, Pengfei Cao, Chenhao Wang +7
With the development of deep learning, natural language processing technology has effectively improved the efficiency of various aspects of the traditional judicial industry. Howev…
Focus on Your Question! Interpreting and Mitigating Toxic CoT Problems in Commonsense Reasoning
Jiachun Li, Pengfei Cao, Chenhao Wang +5
Large language models exhibit high-level commonsense reasoning abilities, especially with enhancement methods like Chain-of-Thought (CoT). However, we find these CoT-like methods l…