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Matching papers

N_0-VTLA: Scaling Vision-Tactile-Language-Action Model with Latent Tactile Tokens

49 upvotes · 26 JUL 2026 · NeoteAI Team, Fudan TEAI Team

This paper introduces a vision-tactile-language-action model that can perform fine-grained manipulation with tactile perception and control, and improve its policy offline from stored data. Practitioners may care because this model can be used to create more versatile and accurate tactile-driven manipulation policies.

vision-tactile-language-action modelscontinual learningoffline reinforcement learningtactile feedbackrobot manipulation

Multi-Turn On-Policy Distillation with Prefix Replay

11 upvotes · 16 JUL 2026 · Baohao Liao, Hanze Dong, Christof Monz et al.

This paper proposes a method to improve on-policy distillation by reusing pre-collected teacher data, allowing for faster training without interacting with the environment. Practitioners may care about this technique because it enables scalable and efficient distillation of complex agent models.

on-policy distillationcontinual learningreinforcement learningagent-environment interactionoffline reinforcement learning