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20242026
most citedEasyJailbreak: A Unified Framework for Jailbreaking Large Language Models

6 citations · 7 across the 13 of their papers we have counts for

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cs.CL2026

AgentV-RL: Scaling Reward Modeling with Agentic Verifier

Jiazheng Zhang, Ziche Fu, Zhiheng Xi +13

Verifiers have been demonstrated to enhance LLM reasoning via test-time scaling (TTS). Yet, they face significant challenges in complex domains. Error propagation from incorrect in…

cs.CL2025

LLMEval-Fair: A Large-Scale Longitudinal Study on Robust and Fair Evaluation of Large Language Models

Ming Zhang, Yujiong Shen, Jingyi Deng +19

Existing evaluation of Large Language Models (LLMs) on static benchmarks is vulnerable to data contamination and leaderboard overfitting, critical issues that obscure true model ca…

cs.CL20251 cited

LLMEval-Med: A Real-world Clinical Benchmark for Medical LLMs with Physician Validation

Ming Zhang, Yujiong Shen, Zelin Li +13

Evaluating large language models (LLMs) in medicine is crucial because medical applications require high accuracy with little room for error. Current medical benchmarks have three…

cs.CL2024

DocFusion: A Unified Framework for Document Parsing Tasks

Mingxu Chai, Ziyu Shen, Chong Zhang +6

Document parsing is essential for analyzing complex document structures and extracting fine-grained information, supporting numerous downstream applications. However, existing meth…

cs.CL2024

Modeling Layout Reading Order as Ordering Relations for Visually-rich Document Understanding

Chong Zhang, Yi Tu, Yixi Zhao +8

Modeling and leveraging layout reading order in visually-rich documents (VrDs) is critical in document intelligence as it captures the rich structure semantics within documents. Pr…

cs.CL20246 cited

EasyJailbreak: A Unified Framework for Jailbreaking Large Language Models

Weikang Zhou, Xiao Wang, Limao Xiong +18

Jailbreak attacks are crucial for identifying and mitigating the security vulnerabilities of Large Language Models (LLMs). They are designed to bypass safeguards and elicit prohibi…