most citedSurgVLM: A Large Vision-Language Model and Systematic Evaluation Benchmark for Surgical Intelligence

2 citations · 3 across the 14 of their papers we have counts for

collaborators

23 papers

cs.CR2025

Casting a SPELL: Sentence Pairing Exploration for LLM Limitation-breaking

Yifan Huang, Xiaojun Jia, Wenbo Guo +4

Large language models (LLMs) have revolutionized software development through AI-assisted coding tools, enabling developers with limited programming expertise to create sophisticat…

cs.CR2025

OmniSafeBench-MM: A Unified Benchmark and Toolbox for Multimodal Jailbreak Attack-Defense Evaluation

Xiaojun Jia, Jie Liao, Qi Guo +11

Recent advances in multi-modal large language models (MLLMs) have enabled unified perception-reasoning capabilities, yet these systems remain highly vulnerable to jailbreak attacks…

cs.CV2025

Shedding Light on VLN Robustness: A Black-box Framework for Indoor Lighting-based Adversarial Attack

Chenyang Li, Wenbing Tang, Yihao Huang +4

Vision-and-Language Navigation (VLN) agents have made remarkable progress, but their robustness remains insufficiently studied. Existing adversarial evaluations often rely on pertu…

cs.CV2025

Beyond Pixels: Semantic-aware Typographic Attack for Geo-Privacy Protection

Jiayi Zhu, Yihao Huang, Yue Cao +5

Large Visual Language Models (LVLMs) now pose a serious yet overlooked privacy threat, as they can infer a social media user's geolocation directly from shared images, leading to u…

cs.CV2025

AutoPrompt: Automated Red-Teaming of Text-to-Image Models via LLM-Driven Adversarial Prompts

Yufan Liu, Wanqian Zhang, Huashan Chen +4

Despite rapid advancements in text-to-image (T2I) models, their safety mechanisms are vulnerable to adversarial prompts, which maliciously generate unsafe images. Current red-teami…

cs.CL2025

SeCon-RAG: A Two-Stage Semantic Filtering and Conflict-Free Framework for Trustworthy RAG

Xiaonan Si, Meilin Zhu, Simeng Qin +7

Retrieval-augmented generation (RAG) systems enhance large language models (LLMs) with external knowledge but are vulnerable to corpus poisoning and contamination attacks, which ca…