3 papers
cs.CL2026
DPlan: Dual-Agent Dynamic Global Planning for Complex Retrieval-Augmented Reasoning
Kangcheng Luo, Tinglang Wu, Yansong Feng
Recent search-augmented LLMs trained with reinforcement learning (RL) can interleave searching and reasoning for multi-hop reasoning tasks. However, they face two critical failure…
cs.CL2025
JUREX-4E: Juridical Expert-Annotated Four-Element Knowledge Base for Legal Reasoning
Huanghai Liu, Quzhe Huang, Qingjing Chen +5
In recent years, Large Language Models (LLMs) have been widely applied to legal tasks. To enhance their understanding of legal texts and improve reasoning accuracy, a promising app…
cs.CL2025
Automating Legal Interpretation with LLMs: Retrieval, Generation, and Evaluation
Kangcheng Luo, Quzhe Huang, Cong Jiang +1
Interpreting the law is always essential for the law to adapt to the ever-changing society. It is a critical and challenging task even for legal practitioners, as it requires metic…