Autoresearchオープンなソースプロジェクトです。AIエージェントが独立してLLMトレーニング実験を実行し、最も優れたモデル変更を保持することができます。

What is Autoresearch and who is it designed for?

Autoresearch is an open-source project that enables AI agents to autonomously run LLM training experiments and retain the best-performing model changes. It's aimed at ML researchers and engineers exploring automated experimentation workflows for large language models.

Is Autoresearch free to use, and can I modify it?

Yes. Autoresearch is open-source, so you can use, inspect, and modify the code according to its license terms. There is no commercial pricing tier described for the project itself, though you'll cover your own compute costs for running training experiments.

What is the main use case for Autoresearch?

The primary use case is automating LLM training experimentation: letting AI agents iteratively propose, run, and evaluate training changes, then keep only the modifications that improve the model. This is useful for hands-off research loops and exploring model improvements at scale.