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20242026
most citedProtecting Copyright of Medical Pre-trained Language Models: Training-Free Backdoor Model Watermarking

1 citations · 2 across the 17 of their papers we have counts for

collaborators

18 papers

cs.CV2026

Trace, Verify, and Correct: A Training-Free Framework for Spatial Reasoning in Multimodal LLMs

Yang Yang, Jiawei Chen, Tairan Chen +1

Although Multimodal Large Language Models (MLLMs) have made substantial progress, their spatial reasoning may still produce intermediate judgments inconsistent with the input image…

cs.CR2026

VertMark: A Unified Training-Free Robust Watermarking Framework for Vertical Domain Pre-trained Language Models

Cong Kong, Xin Cheng, Zhaoxia Yin +3

With the application of vertical domain pre-trained language models (VPLMs) in specialized fields such as medical, finance, and law, model parameters and inference capabilities hav…

cs.CL2026

Skills-Coach: A Self-Evolving Skill Optimizer via Training-Free GRPO

Yu Tian, Jiawei Chen, Lifan Zheng +5

We introduce Skills-Coach, a novel automated framework designed to significantly enhance the self-evolution of skills within Large Language Model (LLM)-based agents. Addressing the…

cs.CV2026

DO-Bench: An Attributable Benchmark for Diagnosing Object Hallucination in Vision-Language Models

JiYang Wang, Jiawei Chen, Mengqi Xiao +3

Object level hallucination remains a central reliability challenge for vision language models (VLMs), particularly in binary object existence verification. Existing benchmarks emph…

cs.CL2026

LCO: LLM-based Constraint Optimization for Safer Agentic LLMs in Real-world Tasks

Jiayong Wan, Jiawei Chen, Zhaoxia Yin +2

Large Language Models (LLMs) are increasingly acting as autonomous agents, but their continuous interaction with the environment can lead to in-context reward hacking (ICRH), a phe…

cs.CV2026

Tex3D: Objects as Attack Surfaces via Adversarial 3D Textures for Vision-Language-Action Models

Jiawei Chen, Simin Huang, Jiawei Du +5

Vision-language-action (VLA) models have shown strong performance in robotic manipulation, yet their robustness to physically realizable adversarial attacks remains underexplored.…