Author

Katsushi Ikeuchi

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Preprint Sep 2026

VLaRL: Augmenting Vision-Language-Action Models with Simulation-Trained Latent-Conditioned Residual RL

Vision-language-action (VLA) models provide broad, instruction-conditioned manipulation behaviors, but their physical execution can remain imprecise during contact-rich interaction. Residual reinforcement learning (RL) can correct such errors while keeping the VLA frozen, but real-robot RL is costly and safety-critical...

Namiko Saito, Kinam Kim, Heecheol Kim et al. · 0 citations

#artificial intelligence Preprint Oct 2026

DiVeR: Decision-Critical Verifier Learning for VLA Test-Time Scaling

Scaling robot data and model capacity has improved Vision-Language-Action (VLA) policies, but further progress is constrained by the high cost of robotic data. Verifier-guided test-time scaling offers an efficient alternative by sampling multiple action candidates and selecting the one most likely to lead to task succe...

Seongheon Park, Heecheol Kim, Shu-Lin Tian et al. · 0 citations