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most citedLLMs-as-Judges: A Comprehensive Survey on LLM-based Evaluation Methods

38 citations · 40 across the 4 of their papers we have counts for

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6 papers · 1 filter

cs.CL20261 cited

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL2025

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…

cs.CL20241 cited

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…

cs.CL202438 cited

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…