5 papers
PoliLegalLM: A Technical Report on a Large Language Model for Political and Legal Affairs
Yuting Huang, Yinghao Hu, Qian Xiao +7
Large language models (LLMs) have achieved remarkable success in general-domain tasks, yet their direct application to the legal domain remains challenging due to hallucinated lega…
P2S: Probabilistic Process Supervision for General-Domain Reasoning Question Answering
Wenlin Zhong, Chengyuan Liu, Yiquan Wu +5
While reinforcement learning with verifiable rewards (RLVR) has advanced LLM reasoning in structured domains like mathematics and programming, its application to general-domain rea…
AppealCase: A Dataset and Benchmark for Civil Case Appeal Scenarios
Yuting Huang, Meitong Guo, Yiquan Wu +6
Recent advances in LegalAI have primarily focused on individual case judgment analysis, often overlooking the critical appellate process within the judicial system. Appeals serve a…
Gold Panning in Vocabulary: An Adaptive Method for Vocabulary Expansion of Domain-Specific LLMs
Chengyuan Liu, Shihang Wang, Lizhi Qing +4
While Large Language Models (LLMs) demonstrate impressive generation abilities, they frequently struggle when it comes to specialized domains due to their limited domain-specific k…
More Than Catastrophic Forgetting: Integrating General Capabilities For Domain-Specific LLMs
Chengyuan Liu, Yangyang Kang, Shihang Wang +5
The performance on general tasks decreases after Large Language Models (LLMs) are fine-tuned on domain-specific tasks, the phenomenon is known as Catastrophic Forgetting (CF). Howe…