Temporal Order Matters for Agentic Memory:
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Temporal Order Matters for Agentic Memory: Segment Trees for Long-Horizon Agents
Announce Type: new Abstract: Long-horizon conversational agents need to interact with users through evolving events, tasks, and goals. Such histories are naturally temporal, yet many existing memory systems organize information primarily by topical similarity and may ignore the order in which events occur. We introduce Segment Tree Memory, or SegTreeMem, a memory architecture that represents conversation history as a temporally ordered Segment Tree over utterances.