Grounded Action Models (GAMs), a new paradigm of robot foundation models built with 3D grounding, are proposed, which can be run autonomously and serve as a low-level controller that a high-level planner controls using its various input modalities, allowing for long-horizon and memory-dependent manipulation.
Ge-Hao Zhang, Weikai Huang, S. Shailesh et al.· 0 citations
Latent Interface Training (LIT), a framework-agnostic two-stage strategy that first establishes a spatial-goal-conditioned action prior without images, then constrains visual conditioning through a pose-supervised latent interface, improves overall LIBERO-Plus success while preserving or improving average LIBERO succes...
Jian-Man Lin, S. Shailesh, Zhong-Yi Luo et al.· 1 citation
This work introduces an adaptive inference-time steering framework that leverages Reinforcement Learning on VLA Latents, and discovers that inference-time steering follows fundamentally different scaling laws under success and failure states, revealing that action diversity is most beneficial when the base VLA is likel...
Derek Ming Siang Tan, S. Shailesh, Srikrishna Iyer et al.· arXiv.org· 0 citations
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