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1,589 papers
DS-VLA is introduced, a dendritic-inspired action architecture that incorporates dendritic spiking dynamics into VLA control to enable modularized feature processing and temporal information integration and demonstrate that integrating brain-inspired computational mechanisms offers a promising architectural prior for r...
When several surfaces are visible along a ray, recovering visible 3D structure from one image requires jointly estimating their presence and metric depth. Depth Any Seen represents these surfaces as image-conditioned multi-Bernoulli depth sets, whose components each contribute one depth or remain absent. Its auxiliary-...
Progress-Heuristicized Inverse Reinforcement Learning (PHIRL), a data-efficient framework that learns robust reward functions by jointly leveraging demonstrations and feedback, uses progress, a feedback modality that describes cumulative task completion.
The results do not establish generalization to other lots or real vehicles, or a formal safety guarantee, and the results do not establish generalization to other lots or real vehicles, or a formal safety guarantee.
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A practical way to build general-purpose manipulation experiments around GPT-6-Astra is suggested: supply machine-readable body descriptions and synchronized demonstrations, and turn useful agent-generated feedback routines into reusable skills, while the agent adapts actions from current images.
These lessons are distill into concrete recommendations for building robot systems that improve themselves, each paired with an experiment that could prove it wrong.
JRDB-AVR is introduced, a benchmark derived from existing real-world JRDB robotics data through a structured question-generation engine that turns this gap between answer accuracy and evidence accuracy in current baselines into an explicit evaluation.
Vision-language-action (VLA) models adapt pretrained vision-language models (VLMs) for closed-loop robot control, transferring their perceptual and semantic capabilities to action prediction. Despite strong in-distribution performance, however, VLAs often degrade under deployment shifts. Adversarial training (AT) offer...
Signal Temporal Logic (STL) enables rigorous verification and control of cyber-physical systems, but writing correct specifications requires expertise that most requirement holders lack. Large language models can translate natural-language (NL) requirements into STL, yet stronger translators alone approach an accuracy...
This work introduces PlanGuard, the first pre-execution detector that evaluates the physical safety of a complete multi-step plan in its current environment, and proposes Strong-Teacher Adaptive Compensation for On-Policy Distillation (STAC-OPD), which provides compact models with adaptive strong-teacher supervision al...
This work investigates robustness to one-step perturbations applied at a single time step per episode and proposes CARE, which dynamically selects the execution length based on consistency with the previously predicted action chunk, which improves robustness with low computational overhead while preserving clean perfor...
Metro-WM is introduced, a hierarchical framework that issues sub-goals by retrieving genuine states from prior experience rather than generating ungrounded latent vectors that achieves superior long-horizon success rates and maintains robust performance under extremely sparse dataset conditions.
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
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