3 papers
cs.CV2026
OVIBench: Benchmarking Online Video Question Answering under Interruption
Naiming Liu, Zhiheng Wu, Shuning Wang +3
Recent vision language models (VLMs) have achieved strong progress in video understanding. However, most existing video QA research and benchmarks still follow an offline, single-r…
cs.CV2026
Beyond Frame Selection: Generative Latent Evidence Aggregation for Long-Video Understanding
Bowen Liu, Shuning Wang, Xinpeng Ding +3
Long-video understanding commonly compresses videos into a small set of frames or visual tokens for answer generation. Existing compact pipelines focus on retaining relevant visual…
cs.CV2026
MedHorizon: Towards Long-context Medical Video Understanding in the Wild
Bodong Du, Bowen Liu, Yang Yu +8
Medical multimodal large language models (MLLMs) have advanced image understanding and short-video analysis, but real clinical review often requires full-procedure video understand…