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AMBER: Training Long-Horizon Web Agents through Append-Only Memory

arXiv:2610.07118v1 Announce Type: new Abstract: Modern language-model agents increasingly interact with external environments over long-horizon, multi-step trajectories, where the accumulated interaction history can quickly exceed practical context budgets. To ensure reliability, agents must mainta…

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  1. 2026-10-07 04:00 · arXiv cs.AI
    AMBER: Training Long-Horizon Web Agents through Append-Only Memory

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