RSI-Anything

RSI-Anything is a domain-general framework that turns world-model predictions and interaction feedback into recursive self-improvement. Built on JEPA-Anything, it connects candidate generation, prediction-guided selection, external evaluation and learning in a shared process. The paper applies this process to code repair, GUI interaction, laboratory planning, reaction optimization and immune science. Each domain supplies its own state, actions, prediction targets and feedback, while using the same cycle of proposing candidates, anticipating consequences, evaluating selected actions and retaining improvements for subsequent rounds.

RSI-Anything: Unlocking Recursive Self-Improvement with World Models