MGRetrieval: Memory-Guided Reflective Retrieval for Long-Term Dialogue Agents
Large Language Models (LLMs) have made significant progress in dialogue, yet redundant memory contexts severely limit their effectiveness in long-term dialogue agents. External memory systems have been proposed to improve memory maintenance. However, these systems mainly rely on one-shot retrieval, which limits their ability to retrieve sufficient and relevant evidence. Although recent methods introduce reflection into retrieval, their retrieval paths are generated by the LLM from limited evidence, leading to unstable retrieval and additional latency overhead. %These limitations highlight the need for effective retrieval mechanisms. To address these limitations, we propose MGRetrieval, a ...
| Authors | Tan Wang, Yunwei Dong |
|---|---|
| Primary category | cs.IR |
| Published | 22 May 2026 |
| Last updated at source | 22 May 2026 |
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