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Tactile feedback integration boosts robot manipulation success rates by over 40% in contact-rich tasks, redefining the limits of vision-language-action models.
Robot actions can serve as powerful geometric supervision, enabling sparse 3D representations that are both reusable and effective across diverse manipulation tasks.
A principled framework for General World Models reveals the limitations of current systems and the architectural requirements for future progress.
VecFormer slashes the computational cost of graph transformers while boosting out-of-distribution generalization by operating attention on quantized "graph tokens" instead of individual nodes.