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20232026
most citedRethinking the Role of Prompting Strategies in LLM Test-Time Scaling: A Perspective of Probability Theory

2 citations · 4 across the 13 of their papers we have counts for

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8 papers · 1 filter

cs.CV2025

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…

cs.CV2025

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…

cs.CR2025

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…

cs.CL2025

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…

cs.CV2025

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…

cs.AI2025★ 2 cited

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…

cs.CV2025

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…

cs.CV2025

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…