Joint Optimization of Reasoning and Dual-Memory for Self-Learning Diagnostic Agent
Clinical expertise improves not only by acquiring medical knowledge, but by accumulating experience that yields reusable diagnostic patterns. Recent LLMs-based diagnostic agents have shown promising progress in clinical reasoning for decision support. However, most approaches treat cases independently, limiting experience reuse and continual adaptation. We propose SEA, a self-learning diagnostic agent with cognitively inspired dual-memory module. We design a reinforcement training framework tailored to our designed agent for joint optimization of reasoning and memory management. We evaluate SEA in two complementary settings. On standard evaluation with MedCaseReasoning dataset, SEA achiev...
| Authors | Bingxuan Li, Simo Du, Yue Guo |
|---|---|
| Primary category | cs.CL |
| Published | 8 April 2026 |
| Last updated at source | 7 August 2026 |
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