collaborators

5 papers

cs.CL2026

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…

cs.CR2026

Search-Time Contamination in Deep Research Agents: Measuring Performance Inflation in Public Benchmark Evaluation

Yongjie Wang, Xinyue Zhang, Kunhong Yao +4

Public benchmarks enable fair and reproducible evaluation of LLM reasoning, but they become fragile for deep research agents that actively search the web during inference. Such age…

cs.CV2026

Do Vision-Language Models Truly Perform Vision Reasoning? A Rigorous Study of the Modality Gap

Yige Xu, Yongjie Wang, Zizhuo Wu +3

Reasoning in vision-language models (VLMs) has recently attracted significant attention due to its broad applicability across diverse downstream tasks. However, it remains unclear…

cs.CR2025

Adversarial Attack-Defense Co-Evolution for LLM Safety Alignment via Tree-Group Dual-Aware Search and Optimization

Xurui Li, Kaisong Song, Rui Zhu +2

Large Language Models (LLMs) have developed rapidly in web services, delivering unprecedented capabilities while amplifying societal risks. Existing works tend to focus on either i…

cs.CL2025

When Retrieval Succeeds and Fails: Rethinking Retrieval-Augmented Generation for LLMs

Yongjie Wang, Yue Yu, Kaisong Song +2

Large Language Models (LLMs) have enabled a wide range of applications through their powerful capabilities in language understanding and generation. However, as LLMs are trained on…