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cs.CV2026
Rethinking Long-Video Efficiency: A Joint Allocation Perspective on Frames, Pixels, and Front-End Latency
Sixun Dong, Wei Li, Andong Deng +4
Efficient long-video understanding with vision-language models (VLMs) is often framed as selecting informative frames or visual tokens at a fixed native resolution. We show that pe…
cs.CV2026
MissingBench-Verified: Probing Vision-Language Models' Inability to Detect Missing Object Parts
Wenqi Marshall Guo, Qingyun Qian, Shiyu Zhou +2
Vision Language Models (VLMs) are well known for hallucinating non-existent objects in images. Objects with missing parts present a unique challenge for VLMs, stemming from both re…