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Grounding AI agents in biological reality: Building blocks for autonomous wet labs
General Science
#로보틱스
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CarryOn: A Dual-Loop Harness for Personalized and Reliable Robot Assistance
While generalist vision-language-action (VLA) models have enabled diverse open-world manipulation, real-world robotic assistance requires two critical capabilities they currently lack: personalization and reliable execution.
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PAIR: Bridging Perception and Action in Vision-Language-Action Models
Vision-language-action (VLA) models map visual observations and language instructions to continuous robot actions.
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CoDA: Co-Evolution of Data Engines and Action Policies
Generative simulation can automate robot environment construction, but physically valid environments are not necessarily useful for training.
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VLA-Δ: Learning Physical State Transition for Vision-Language-Action Models
Vision-language-action (VLA) models transfer semantic knowledge acquired through vision-language pretraining to robot control, achieving strong performance across various benchmarks.
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PINT: A Unified Model with Shared Predictive Intent for Robot Manipulation
Generalist robot manipulation can benefit from pretrained vision-language models (VLMs) for semantic reasoning and video generation models (VGMs) for world modeling.
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SimForcing: Distilling Simulation Motion Priors into Real-Domain Robot World Models
Action-conditioned robot world models must respond precisely to robot trajectories while preserving realistic visual dynamics, yet learning both from heterogeneous robot videos remains challenging.