3 papers
cs.CV2025
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…
cs.CV2025
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…
cs.LG2025
Robust Spatiotemporal Forecasting Using Adaptive Deep-Unfolded Variational Mode Decomposition
Osama Ahmad, Lukas Wesemann, Fabian Waschkowski +1
Accurate spatiotemporal forecasting is critical for numerous complex systems but remains challenging due to complex volatility patterns and spectral entanglement in conventional gr…