CORAL is a robust, lightweight infrastructure for multi-agent autonomous self-evolution, built for autoresearch.

A curated list of awesome autonomous researcher frameworks

Autonomous fine-tuning of time series foundation models via AI-driven experiment loops

Karpathy's Autoresearch modified to rungames such as Connect Four

A codex plugin for running optimization loops inside a codebase. It is useful when you have a measurable target and many possible changes to try: test runtime, build speed, bundle size, model loss, Lighthouse scores, memory use, query latency, or any other metric you can print from a script.

General-purpose autonomous research lab — PI and PhD agents run experiments, analyze results, and write papers

Explore curated AutoResearch use cases with optimization traces and open source implementations for each entry