3 papers
cs.LG2025
A Unified Multi-Agent Framework for Universal Multimodal Understanding and Generation
Jiulin Li, Ping Huang, Yexin Li +3
Real-world multimodal applications often require any-to-any capabilities, enabling both understanding and generation across modalities including text, image, audio, and video. Howe…
cs.CV2025
Breaking Down Video LLM Benchmarks: Knowledge, Spatial Perception, or True Temporal Understanding?
Bo Feng, Zhengfeng Lai, Shiyu Li +4
Existing video understanding benchmarks often conflate knowledge-based and purely image-based questions, rather than clearly isolating a model's temporal reasoning ability, which i…
cs.CV2025
StreamBridge: Turning Your Offline Video Large Language Model into a Proactive Streaming Assistant
Haibo Wang, Bo Feng, Zhengfeng Lai +6
We present StreamBridge, a simple yet effective framework that seamlessly transforms offline Video-LLMs into streaming-capable models. It addresses two fundamental challenges in ad…