1 citations · 1 across the 12 of their papers we have counts for
13 papers
SkillScaffold: Scaffolding Agentic Reinforcement Learning with Policy-Adaptive Skill Credit Assignment and Selective Injection
Wenlin Zhong, Hao Wang, Kun Yuan +6
Agentic reinforcement learning (RL) enables large language models (LLMs) to learn from multi-turn interactions with verifiable outcomes. Textual skills can improve exploration by d…
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…
WisdomInterrogatory (LuWen): An Open-Source Legal Large Language Model Technical Report
Yiquan Wu, Yuhang Liu, Yifei Liu +4
Large language models have demonstrated remarkable capabilities across a wide range of natural language processing tasks, yet their application in the legal domain remains challeng…
SIGHT: Reinforcement Learning with Self-Evidence and Information-Gain Diverse Branching for Search Agent
Wenlin Zhong, Jinluan Yang, Yiquan Wu +3
Reinforcement Learning (RL) has empowered Large Language Models (LLMs) to master autonomous search for complex question answering. However, particularly within multi-turn search sc…
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…
Universal Legal Article Prediction via Tight Collaboration between Supervised Classification Model and LLM
Xiao Chi, Wenlin Zhong, Yiquan Wu +4
Legal Article Prediction (LAP) is a critical task in legal text classification, leveraging natural language processing (NLP) techniques to automatically predict relevant legal arti…
MM-ARC: Multimodal Adaptive Routing of Capital with Robustness-Audited Strategy Pools
Yang Chen, Yuchen Cao, Jacky Keung +7
Financial trading systems must convert multimodal market history into executable positions while limiting overfitting from repeated strategy search. We introduce MM-ARC (MultiModal…
ClaimGen-CN: A Large-scale Chinese Dataset for Legal Claim Generation
Siying Zhou, Yiquan Wu, Hui Chen +6
Legal claims refer to the plaintiff's demands in a case and are essential to guiding judicial reasoning and case resolution. While many works have focused on improving the efficien…
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…
Xinyu: An Efficient LLM-based System for Commentary Generation
Yiquan Wu, Bo Tang, Chenyang Xi +13
Commentary provides readers with a deep understanding of events by presenting diverse arguments and evidence. However, creating commentary is a time-consuming task, even for skille…
From Graph to Word Bag: Introducing Domain Knowledge to Confusing Charge Prediction
Ang Li, Qiangchao Chen, Yiquan Wu +4
Confusing charge prediction is a challenging task in legal AI, which involves predicting confusing charges based on fact descriptions. While existing charge prediction methods have…
Enhancing Court View Generation with Knowledge Injection and Guidance
Ang Li, Yiquan Wu, Yifei Liu +3
Court View Generation (CVG) is a challenging task in the field of Legal Artificial Intelligence (LegalAI), which aims to generate court views based on the plaintiff claims and the…
Precedent-Enhanced Legal Judgment Prediction with LLM and Domain-Model Collaboration
Yiquan Wu, Siying Zhou, Yifei Liu +6
Legal Judgment Prediction (LJP) has become an increasingly crucial task in Legal AI, i.e., predicting the judgment of the case in terms of case fact description. Precedents are the…