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Evidence-Backed Video Question Answering
一篇关于视频问答的创新论文，强调利用证据推理来提升答案的准确性与可解释性。
arXiv:2607.11862v1 Announce Type: cross Abstract: Current Video Large Language Models (Video LLMs) excel in question answering (QA) but largely operat…
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Training LLMs with Reinforcement Learning over Digital Twin Representations for Reasoning-Intensive Surgical VideoQA
用强化学习与数字孪生表示训练大模型，挑战高推理难度的手术视频问答，开启AI医疗新方向。
arXiv:2606.17279v1 Announce Type: new Abstract: Surgical video question answering requires multi-step reasoning across semantic, spatial, and temporal…
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Answer Self-Consistency with Margin-Triggered Question Re-Arbitration for the CVPR 2026 VidLLMs Challenge
CVPR 2026视频大模型挑战赛新方案：用边际触发问题重仲裁提升回答自一致性，精准优化视频问答可靠性。
arXiv:2606.04323v1 Announce Type: new Abstract: In this report, we present our solution for Track 2 of the CVPR 2026 VidLLMs Challenge. This track eva…
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MuKV: Multi-Grained KV Cache Compression for Long Streaming Video Question-Answering
多粒度KV缓存压缩新方法，大幅降低长流视频问答的内存开销，CVPR'26收录，代码开源。
arXiv:2605.22269v1 Announce Type: new Abstract: Long streaming video QA remains challenging due to growing visual tokens and limited reasoning length …