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MEMO: Multimodal Evidence Memory Organization for Long-Horizon LLM Agents

arXiv · AI, language, vision and robotics · article · Sep 7, 2026 · UTC

Long-running LLM agents rely on external memory to store and reuse information beyond a single context window, yet there is a fundamental tension between the continuous accumulation of interaction trajectories and the limited context capacity. The key challenge in agent memory is therefore not only to retrieve relevant records, but also to select necessary evidence under a given budget and organize it in an appropriate modality. Existing memory readout methods mainly use textual or visual forms. Text preserves high fidelity, but its linear token representation makes contents with different imp

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