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CoreMem: Riemannian Retrieval and Fisher-Guided Distillation for Long-Term Memory in Dialogue Agents

arXiv cs.CL ↗ · 2026-06-18 Cached

CoreMem proposes a resource-efficient edge-cloud memory architecture for dialogue agents, using Riemannian retrieval with a Fisher-Rao metric and Fisher-guided discrete token distillation to achieve strong accuracy improvements within an 8 GB VRAM budget.

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