VideoLoop: Looped Working Memory Against Semantic Thrashing in Long-Form Video Agents
Long-form video understanding requires multimodal agents to iteratively gather evidence over many reasoning steps. However, most existing agentic methods suffer from semantic thrashing: as append-only working memory grows, attention to key evidence collapses, and the agent loses access to what it has already found. First, we provide a structural argument showing that append-only memory can incorporate newly observed target evidence, but cannot remove accumulated noise or prevent ordered context growth without a rewrite operator. Second, motivated by this analysis, we propose VideoLoop, a multimodal agent with two coupled loops. The outer loop reasons over the video and the inner loop, aft...
| Authors | Jianming Xu, Jinfa Huang, Jingyang Lin et al. |
|---|---|
| Primary category | cs.CV |
| Published | 29 September 2026 |
| Last updated at source | 30 September 2026 |
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