CoVR-R:Reason-Aware Composed Video Retrieval
Composed Video Retrieval (CoVR) aims to find a target video given a reference video and a textual modification. Prior work assumes the modification text fully specifies the visual changes, overlooking after-effects and implicit consequences (e.g., motion, state transitions, viewpoint or duration cues) that emerge from the edit. We argue that successful CoVR requires reasoning about these after-effects. We introduce a reasoning-first, zero-shot approach that leverages large multimodal models to (i) infer causal and temporal consequences implied by the edit, and (ii) align the resulting reasoned queries to candidate videos without task-specific finetuning. To evaluate reasoning in CoVR, we ...
| Authors | Omkar Thawakar, Dmitry Demidov, Vaishnav Potlapalli et al. |
|---|---|
| Primary category | cs.CV |
| Published | 20 March 2026 |
| Last updated at source | 9 June 2026 |
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