2 citations · 4 across the 13 of their papers we have counts for
15 papers
ScenePercept: Scenario-Conditioned Perceptual Assessment of Real-World User-Generated Content Images
Shuhan Xia, Yu Chen, Xiang Wang +3
The rapid development of mobile imaging and social platforms has led to explosive growth in user-generated content images, making their systematic and comprehensive perceptual asse…
DiverAge: Reliable Pluralistic Face Aging with Cross-Age Identity Relation Guidance
Yueying Zou, Peipei Li, Qianrui Teng +2
Face aging plays an important role in long-term biometric analysis, cross-age identity verification, and forensic identity analysis. Since the same subject may exhibit multiple pla…
GenVideoLens: Where LVLMs Fall Short in AI-Generated Video Detection?
Yueying Zou, Pei Pei Li, Zekun Li +4
In recent years, AI-generated videos have become increasingly realistic and sophisticated. Meanwhile, Large Vision-Language Models (LVLMs) have shown strong potential for detecting…
AgentHallu: Benchmarking Automated Hallucination Attribution of LLM-based Agents
Xuannan Liu, Xiao Yang, Zekun Li +2
As LLM-based agents operate over sequential multi-step reasoning, hallucinations arising at intermediate steps risk propagating along the trajectory, thus degrading overall reliabi…
AVFakeBench: A Comprehensive Audio-Video Forgery Detection Benchmark for AV-LMMs
Shuhan Xia, Peipei Li, Xuannan Liu +3
The threat of Audio-Video (AV) forgery is rapidly evolving beyond human-centric deepfakes to include more diverse manipulations across complex natural scenes. However, existing ben…
SpineBench: Benchmarking Multimodal LLMs for Spinal Pathology Analysis
Chenghanyu Zhang, Zekun Li, Peipei Li +5
With the increasing integration of Multimodal Large Language Models (MLLMs) into the medical field, comprehensive evaluation of their performance in various medical domains becomes…
MCP Security Bench (MSB): Benchmarking Attacks Against Model Context Protocol in LLM Agents
Dongsen Zhang, Zekun Li, Xu Luo +3
The Model Context Protocol (MCP) standardizes how large language model (LLM) agents discover, describe, and call external tools. While MCP unlocks broad interoperability, it also e…
T^2Agent A Tool-augmented Multimodal Misinformation Detection Agent with Monte Carlo Tree Search
Xing Cui, Yueying Zou, Zekun Li +4
Real-world multimodal misinformation often arises from mixed forgery sources, requiring dynamic reasoning and adaptive verification. However, existing methods mainly rely on static…
Video-SafetyBench: A Benchmark for Safety Evaluation of Video LVLMs
Xuannan Liu, Zekun Li, Zheqi He +6
The increasing deployment of Large Vision-Language Models (LVLMs) raises safety concerns under potential malicious inputs. However, existing multimodal safety evaluations primarily…
Rethinking the Role of Prompting Strategies in LLM Test-Time Scaling: A Perspective of Probability Theory
Yexiang Liu, Zekun Li, Zhi Fang +3
Recently, scaling test-time compute on Large Language Models (LLM) has garnered wide attention. However, there has been limited investigation of how various reasoning prompting str…
ID-Cloak: Crafting Identity-Specific Cloaks Against Personalized Text-to-Image Generation
Qianrui Teng, Xing Cui, Xuannan Liu +4
Personalized text-to-image models allow users to generate images of new concepts from several reference photos, thereby leading to critical concerns regarding civil privacy. Althou…
Survey on AI-Generated Media Detection: From Non-MLLM to MLLM
Yueying Zou, Peipei Li, Zekun Li +5
The proliferation of AI-generated media poses significant challenges to information authenticity and social trust, making reliable detection methods highly demanded. Methods for de…
Jailbreak Attacks and Defenses against Multimodal Generative Models: A Survey
Xuannan Liu, Xing Cui, Peipei Li +6
The rapid evolution of multimodal foundation models has led to significant advancements in cross-modal understanding and generation across diverse modalities, including text, image…
Localize, Understand, Collaborate: Semantic-Aware Dragging via Intention Reasoner
Xing Cui, Peipei Li, Zekun Li +3
Flexible and accurate drag-based editing is a challenging task that has recently garnered significant attention. Current methods typically model this problem as automatically learn…
InstaStyle: Inversion Noise of a Stylized Image is Secretly a Style Adviser
Xing Cui, Zekun Li, Pei Pei Li +3
Stylized text-to-image generation focuses on creating images from textual descriptions while adhering to a style specified by a few reference images. However, subtle style variatio…