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Proactive Memory (ProactMem), which organizes history into recent events, temporal trajectories, and behavioral regularities, is proposed, which organizes history into recent events, temporal trajectories, and behavioral regularities.
Hierarchical Residual Policy Optimization (HRPO), a post-training framework that converts item-level outcomes into dense, token-aligned learning signals for conservative token-wise improvement, is proposed.
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