38 citations · 67 across the 44 of their papers we have counts for
44 papers
GenRubric: Self-Evolving Rubric Generation for Scalable LLM Evaluation
Yifan Chen, Haitao Li, Qingyao Ai +4
Large language models are increasingly used as scalable evaluators for open-ended tasks. However, many LLM judges derive query-specific criteria during scoring, leaving the evaluat…
Different Feedback, Different Updates: Selective Self-Learning from User Interactions for Large Language Models
Xuancheng Li, Xuanchen Li, Haitao Li +6
User feedback offers natural supervision for persistent LLM improvement, but a single message may support multiple behavioral changes with different scopes of generalization. We in…
Civil Court Simulation with Large Language Models
Yifan Chen, Haitao Li, Kaiyuan Zhang +3
Court simulation bridges legal education and judicial practice, yet human-based simulations are costly and difficult to scale. Large language models (LLMs) offer a scalable alterna…
AnyAudio-Judge: A Dynamic Rubric-Based Benchmark and Evaluator for Audio Instruction Following
Haitao Li, Tian Tan, Yuguang Yang +2
The rapid advancement of instruction-guided audio generation has highlighted the critical need for robust alignment evaluation. Current automated evaluation methods heavily rely on…
LexRubric: A Rubric-Guided Diagnostic Benchmark for Open-Ended Legal Tasks
Yifan Chen, Haitao Li, Yiran Hu +6
As large language models (LLMs) are increasingly applied to real-world legal tasks, evaluating the reliability of their open-ended legal responses has become essential. These tasks…
Benchmarking LLM-as-a-Judge for Long-Form Output Evaluation
Junjie Chen, Yuxi Dong, Haitao Li +5
As large language models (LLMs) are increasingly used for long-form generation, reliably evaluating long-form outputs has become a critical challenge. LLM-as-a-judge offers a scala…
UnityMAS-O: A General RL Optimization Framework for LLM-Based Multi-Agent Systems
Yiqun Chen, Wei Yang, Erhan Zhang +14
LLM-based multi-agent systems decompose complex tasks into interacting roles, but most remain manually orchestrated by prompts, tools, and control rules, while agents are rarely op…
ATACompressor: Adaptive Task-Aware Compression for Efficient Long-Context Processing in LLMs
Xuancheng Li, Haitao Li, Yujia Zhou +2
Long-context inputs in large language models (LLMs) often suffer from the "lost in the middle" problem, where critical information becomes diluted or ignored due to excessive lengt…
LegalOne: A Family of Foundation Models for Reliable Legal Reasoning
Haitao Li, Yifan Chen, Shuo Miao +13
While Large Language Models (LLMs) have demonstrated impressive general capabilities, their direct application in the legal domain is often hindered by a lack of precise domain kno…
Multi-Source Retrieval and Reasoning for Legal Sentencing Prediction
Junjie Chen, Haitao Li, Qilei Zhang +9
Legal judgment prediction (LJP) aims to predict judicial outcomes from case facts and typically includes law article, charge, and sentencing prediction. While recent methods perfor…
Beyond Experience Retrieval: Learning to Generate Utility-Optimized Structured Experience for Frozen LLMs
Xuancheng Li, Haitao Li, Yujia Zhou +2
Large language models (LLMs) are largely static and often redo reasoning or repeat mistakes. Prior experience reuse typically relies on external retrieval, which is similarity-base…
Evaluation of Large Language Models in Legal Applications: Challenges, Methods, and Future Directions
Yiran Hu, Huanghai Liu, Chong Wang +15
Large language models (LLMs) are being increasingly integrated into legal applications, including judicial decision support, legal practice assistance, and public-facing legal serv…
MulFeRL: Enhancing Reinforcement Learning with Verbal Feedback in a Multi-turn Loop
Xuancheng Li, Haitao Li, Yujia Zhou +2
Reinforcement Learning with Verifiable Rewards (RLVR) is widely used to improve reasoning across domains, but outcome-only scalar rewards are often sparse and uninformative. This l…
JustEva: A Toolkit to Evaluate LLM Fairness in Legal Knowledge Inference
Zongyue Xue, Siyuan Zheng, Shaochun Wang +8
The integration of Large Language Models (LLMs) into legal practice raises pressing concerns about judicial fairness, particularly due to the nature of their "black-box" processes.…
Simulating Dispute Mediation with LLM-Based Agents for Legal Research
Junjie Chen, Haitao Li, Minghao Qin +6
Legal dispute mediation plays a crucial role in resolving civil disputes, yet its empirical study is limited by privacy constraints and complex multivariate interactions. To addres…
Chinese Court Simulation with LLM-Based Agent System
Kaiyuan Zhang, Jiaqi Li, Yueyue Wu +7
Mock trial has long served as an important platform for legal professional training and education. It not only helps students learn about realistic trial procedures, but also provi…
LLMs on Trial: Evaluating Judicial Fairness for Large Language Models
Yiran Hu, Zongyue Xue, Haitao Li +10
Large Language Models (LLMs) are increasingly used in high-stakes fields where their decisions impact rights and equity. However, LLMs' judicial fairness and implications for socia…
SelfRACG: Enabling LLMs to Self-Express and Retrieve for Code Generation
Qian Dong, Jia Chen, Qingyao Ai +6
Existing retrieval-augmented code generation (RACG) methods typically use an external retrieval module to fetch semantically similar code snippets used for generating subsequent fr…
Overview of the NTCIR-18 Automatic Evaluation of LLMs (AEOLLM) Task
Junjie Chen, Haitao Li, Zhumin Chu +2
In this paper, we provide an overview of the NTCIR-18 Automatic Evaluation of LLMs (AEOLLM) task. As large language models (LLMs) grow popular in both academia and industry, how to…
Qilin: A Multimodal Information Retrieval Dataset with APP-level User Sessions
Jia Chen, Qian Dong, Haitao Li +9
User-generated content (UGC) communities, especially those featuring multimodal content, improve user experiences by integrating visual and textual information into results (or ite…
LexRAG: Benchmarking Retrieval-Augmented Generation in Multi-Turn Legal Consultation Conversation
Haitao Li, Yifan Chen, Yiran Hu +7
Retrieval-augmented generation (RAG) has proven highly effective in improving large language models (LLMs) across various domains. However, there is no benchmark specifically desig…
CaseGen: A Benchmark for Multi-Stage Legal Case Documents Generation
Haitao Li, Jiaying Ye, Yiran Hu +8
Legal case documents play a critical role in judicial proceedings. As the number of cases continues to rise, the reliance on manual drafting of legal case documents is facing incre…
LegalAgentBench: Evaluating LLM Agents in Legal Domain
Haitao Li, Junjie Chen, Jingli Yang +10
With the increasing intelligence and autonomy of LLM agents, their potential applications in the legal domain are becoming increasingly apparent. However, existing general-domain b…
LLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods
Haitao Li, Qian Dong, Junjie Chen +5
The rapid advancement of Large Language Models (LLMs) has driven their expanding application across various fields. One of the most promising applications is their role as evaluato…