Preprint
Aug 2026
CounterAlign: Counterfactual Supervision for Vision-Language-Action Models
This work synthesizes counterfactual instruction-observation-action tuples from the dataset and combines them with adversarial discriminator training to learn an instruction-grounded reward model for offline RL, without collecting additional rollouts or annotations.
Haruo Kondoh, Keita Ota, Asako Kanezaki et al.
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