3 papers
cs.AI2025
Configurable multi-agent framework for scalable and realistic testing of llm-based agents
Sai Wang, Senthilnathan Subramanian, Mudit Sahni +6
Large-language-model (LLM) agents exhibit complex, context-sensitive behaviour that quickly renders static benchmarks and ad-hoc manual testing obsolete. We present Neo, a configur…
cs.CV2025
EventVAD: Training-Free Event-Aware Video Anomaly Detection
Yihua Shao, Haojin He, Sijie Li +11
Video Anomaly Detection~(VAD) focuses on identifying anomalies within videos. Supervised methods require an amount of in-domain training data and often struggle to generalize to un…
cs.CL2025
Beyond Single Frames: Can LMMs Comprehend Temporal and Contextual Narratives in Image Sequences?
Xiaochen Wang, Heming Xia, Jialin Song +9
Large Multimodal Models (LMMs) have achieved remarkable success across various visual-language tasks. However, existing benchmarks predominantly focus on single-image understanding…