MUSE: Multi-Level Memory with Selective Runtime Injection for Scientific Coding Agents

MUSE is a memory management framework for scientific coding agents that combines multi-level memory—global, approach-level, and implementation-level—with selective runtime injection. The agent starts with global and problem-matched approach-level memory, then during execution it retrieves implementation-level memory and an LLM gate decides whether to inject relevant experience as review advice. Experiments on four benchmarks in numerical problem solving, kernel optimization, and scientific software repair show that MUSE outperforms retrieval and memory baselines, and ablations confirm the benefits of the multi-level design and gated injection.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv AI.

• llms
• agents
• benchmarks