SOURCE-LINKED INTELLIGENCE
CueMem: Cue-Guided Context Reconstruction for Long-Term Conversational Memory
Long-term conversational agents must answer user queries by recalling information from extended dialogue histories, yet directly using the full history is costly and often unreliable, while compressed memory units may lose fine-grained evidence needed for question answering. Motivated by the reconstructive view of autobiographical memory, we propose CueMem, a cue-guided framework that treats extracted memory records as retrieval cues rather than self-contained evidence and reconstructs query-relevant dialogue context from their source turns. During memory construction, CueMem extracts fine-gra
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-11T02:27:22.000Z
First collected: 2026-09-20T18:42:18.733Z. This is not the publication date.