9 papers
High-Entropy Tokens as Multimodal Failure Points in Vision-Language Models
Mengqi He, Xinyu Tian, Xin Shen +4
Vision-language models (VLMs) achieve remarkable performance but remain vulnerable to adversarial attacks. Entropy, as a measure of model uncertainty, is highly correlated with VLM…
SkillFlow:Benchmarking Lifelong Skill Discovery and Evolution for Autonomous Agents
Ziao Zhang, Kou Shi, Shiting Huang +13
As the capability frontier of autonomous agents continues to expand, they are increasingly able to complete specialized tasks through plug-and-play external skills. Yet current ben…
Breaking Block Boundaries: Anchor-based History-stable Decoding for Diffusion Large Language Models
Shun Zou, Yong Wang, Zehui Chen +4
Diffusion Large Language Models (dLLMs) have recently become a promising alternative to autoregressive large language models (ARMs). Semi-autoregressive (Semi-AR) decoding is widel…
All Roads Lead to Rome: Incentivizing Divergent Thinking in Vision-Language Models
Xinyu Tian, Shu Zou, Zhaoyuan Yang +3
Recent studies have demonstrated that Reinforcement Learning (RL), notably Group Relative Policy Optimization (GRPO), can intrinsically elicit and enhance the reasoning capabilitie…
More Thought, Less Accuracy? On the Dual Nature of Reasoning in Vision-Language Models
Xinyu Tian, Shu Zou, Zhaoyuan Yang +5
Reasoning has emerged as a pivotal capability in Large Language Models (LLMs). Through Reinforcement Learning (RL), typically Group Relative Policy Optimization (GRPO), these model…
Unlocking Vision-Language Models for Video Anomaly Detection via Fine-Grained Prompting
Shu Zou, Xinyu Tian, Lukas Wesemann +3
Prompting has emerged as a practical way to adapt frozen vision-language models (VLMs) for video anomaly detection (VAD). Yet, existing prompts are often overly abstract, overlooki…