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Learning Spatiotemporal Sensitivity in Video LLMs via Counterfactual Reinforcement Learning
Video large language models (Video LLMs) can achieve strong video-QA accuracy without reliably tracking spatiotemporal dynamics. A model may answer a motion question from static cues, for example, and give the same prediction even after the underlying motion is reversed. Correctness-based reinforcem
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