# Intra-VLM Representation Refinement (IVRR)

Axiom-0 uses hierarchical self-refinement to improve both the vision-language model's internal representations and the conditioning before action generation, reaching 62.32% overall success on RoboCasa365, 4.22 percentage points above the highest published leaderboard score of 58.1% from Paimon-0.

Axiom-0 uses hierarchical self-refinement to improve both the vision-language model's internal representations and the conditioning before action generation, reaching 62.32% overall success on RoboCasa365, 4.22 percentage points above the highest published leaderboard score of 58.1% from Paimon-0.