MemRouter: Memory-as-Embedding Routing for Long-Term Conversational Agents
Long-term conversational agents must decide which turns to store in external memory, yet recent systems rely on autoregressive LLM generation at every turn to make that decision. We present MemRouter, a write-side memory router that decouples memory admission from the downstream answer backbone and replaces per-turn memory-management decoding with an embedding-based routing policy. MemRouter encodes each turn together with recent context, projects the resulting embeddings through a frozen LLM backbone, and predicts whether the turn should be stored using lightweight classification heads while training only 12M parameters. Under a controlled matched-harness comparison on LoCoMo, where the ...
| Authors | Tianyu Hu, Weikai Lin, Weizhi Zhang et al. |
|---|---|
| Primary category | cs.CL |
| Published | 1 May 2026 |
| Last updated at source | 1 May 2026 |
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