Yunhong Wang

While large language model–powered agents can self-evolve by accumulating experience or by dynamically creating new assets (i.e., tools or expert agents), existing frameworks typically treat these two evolutionary processes in isolation. This separation overlooks their intrinsic interdependence:...

Recent advancements in Multimodal Large Language Models (MLLMs) have achieved significant success in understanding static pre-recorded video scenarios (e.g., event-centric or narrative-driven content). However, existing MLLMs are largely trained on datasets restricted to static content due to the...