Category
1,589 papers
This work builds on the density-free kinetic-energy regularizer of FLAC, a recent reward-only method, and proposes Reparameterized Augmented-Lagrangian Flow Actor with Least Energy (RAFALE), an off-policy actor-critic method for safe RL.
SMBAR is a continual learning algorithm that prevents catastrophic forgetting during VLA finetuning without requiring access to the demonstrations of any previously learned task, and is cast as a constrained optimization problem and solved with the method of multipliers.
A deterministic multi-dataset predicate framework that derives driving-scene semantics from measurable geometric, kinematic, temporal, map, and traffic-control evidence is introduced and deterministic predicates provide a consistent and traceable semantic representation and, under oracle grounding, can reduce visual de...
Three complementary design requirements motivate the present formulation: an explicit force-related constraint, compensation for steady error under persistent loading, and a prediction model that can incorporate trajectory and actuator information.
Reach audiences
Advertise in front of researchers, engineers, and readers.
This work aggregates patch features from all views onto a single equirectangular panoramic canvas, and introduces a spatial pretraining curriculum by procedurally placing patch features of objects at chosen 3D world positions on an otherwise empty canvas, generating on-the-fly supervision spanning a broad range of spat...
Language models trained on large-scale vision-language data have demonstrated strong potential for embodied agents. Harnessing models through embodied tools use offers a promising alternative to end-to-end vision-language-action systems by combining high-level reasoning with external modules for perception, planning, a...
Vault is a framework that couples one-step latent generation with sample-based reinforcement learning guidance, and achieves state-of-the-art performance at real-time inference cost, reaching state-of-the-art performance at real-time inference cost.
Offline goal-conditioned reinforcement learning requires both long-horizon reachability estimates and local action comparisons. Dual goal representations provide value fields that capture global goal reachability, but they do not directly specify which action should be preferred at a given state. We propose Dual Advant...
Factorized Contrastive Abstractions for Transferable IRL (ConTraIRL), a framework that enables compositional reward transfer by learning decoupled latent representations of these two factors, is proposed.
This work formalizes this prediction-control interface, separate the scalar trigger from its channel-wise diagnostic log, and establishes that an all-pairs displacement term is redundant within a maximum that already contains the corresponding one-step term.
Future Forward Dynamics Causal Attention (FFDC), a lightweight verifier that reasons over predicted actions, predicted visual dynamics, real observations, and instruction-conditioned semantics, is proposed that allows continued execution when a plan remains reliable and triggers replanning when its validity deteriorate...
Existing robot video world models are typically trained with low-level objectives such as reconstruction and perceptual similarity, which are poorly aligned with the capabilities that matter most for robot decision making, including instruction following, manipulation success, and physical plausibility. They also suffe...
A Blog post by Ai2 on Hugging Face
A new system identifies and corrects unreliable object descriptions stored in a robot’s memory, improving the robot’s ability to interact with its environment.
Discover Gemini 4 Argon for robotics: leading the ERQA benchmark with physical reasoning, zero-shot control, Real2Sim, and agentic workflows.
Robots are getting smarter, but how can their hardware match that growth? New Microsoft Research findings show that moving AI inference beyond the robot can improve task success, boost efficiency, and support more advanced physical AI workloads. The post Offloaded inference for real-world physical AI robotics appeared first on Microsoft Research.
A Blog post by Amazon on Hugging Face
We use cookies to run the site and, with your consent, for analytics and to show ads. See our Cookie Policy.
