LIBERO-RIG: A Hardware-Setup Robustness Benchmark for Vision-Language-Action Models
Robot policies are expected to generalize across deployment environments, including variations in the robot itself: c...
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Robot policies are expected to generalize across deployment environments, including variations in the robot itself: c...
Multi-objective molecular optimization is a critical process in drug discovery that aims to modify a given molecule t...
Reinforcement learning with verifiable rewards (RLVR) relies on costly model-generated responses, motivating larger r...
How can we build an agent that thinks beyond human language, yet still acts through it in the external environment? M...
Generating information-rich visual artifacts such as slides, posters, and dashboards as code is appealing because the...
Reasoning models achieve strong performance through long chains of thought (CoT), but often spend more tokens than ne...
Long-horizon agents have drawn growing attention for their ability to work autonomously -- from hours to days -- on e...
How should demonstration quality be used during vision-language-action (VLA) pretraining to improve performance after...
Agentic robotics places a large language model (LLM) agent in the robot control loop, where it composes perception, m...
Vision-language-action (VLA) policies excel at generalist robotic manipulation but generate actions without explicitl...
City-scale 3D grounding is commonly formulated as candidate ranking, which requires precomputed instance proposals an...
Sparse-to-dense motion completion recovers dense mesh motion from sparse vertex displacements. Residual priors traine...