6 papers
GuideMe: Multi-Domain Task Guidance and Intervention in Streaming Video
Fang Liu, Jinpeng Chen, Ke Xu +7
While multimodal Large Language Models (MLLMs) excel at offline video understanding, an interesting question of how far they are from serving as a real-time procedural coach remain…
X-Stream: Exploring MLLMs as Multiplexers for Multi-Stream Understanding
Peiwen Sun, Xudong Lu, Huadai Liu +10
While video streaming understanding has made significant strides, real-world applications, such as live sports broadcasting, autonomous driving, and multi-screen collaboration, inh…
CASTLE2026 Team WDL Technical Report
Zhengyang Li, Zhenglin Du, Yi Wen +3
The CASTLE Challenge @ EgoVis 2026 evaluates long-form egocentric video question answering over 600+ hours of multi-perspective recordings. Each four-choice question requires evide…
AURA: Always-On Understanding and Real-Time Assistance via Video Streams
Xudong Lu, Yang Bo, Jinpeng Chen +9
Video Large Language Models (VideoLLMs) have achieved strong performance on many video understanding tasks, but most existing systems remain offline and are not well-suited for liv…
ALLVB: All-in-One Long Video Understanding Benchmark
Xichen Tan, Yuanjing Luo, Yunfan Ye +2
From image to video understanding, the capabilities of Multi-modal LLMs (MLLMs) are increasingly powerful. However, most existing video understanding benchmarks are relatively shor…
RAG-Adapter: A Plug-and-Play RAG-enhanced Framework for Long Video Understanding
Xichen Tan, Yunfan Ye, Yuanjing Luo +3
Multi-modal Large Language Models (MLLMs) capable of video understanding are advancing rapidly. To effectively assess their video comprehension capabilities, long video understandi…