Combee: Scaling Prompt Learning for Self-Improving Language Model Agents

Combee is a new framework that scales prompt learning for self‑improving language model agents by enabling many agents to run in parallel while learning from their combined traces. It uses parallel scans, an augmented shuffle mechanism, and a dynamic batch size controller to maintain quality and reduce delay. Experiments on AppWorld, Terminal‑Bench, Formula, and FiNER show up to 17× speedup over prior methods with comparable or better accuracy at similar cost.

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