arXiv AI
Jun 8
Planning-aligned Token Compression for Long-Context Autonomous Driving
arXiv:2606. 07464v1 Announce Type: cross Abstract: Monolithic vision-action models represent an emerging paradigm in autonomous driving.
Robotics and embodied AI
Manipulation, locomotion, sim-to-real transfer and autonomous driving: learning systems that have to survive physics.
arXiv AI
Jun 8
Endogenous Resistance to Activation Steering in Language Models
arXiv:2602. 06941v2 Announce Type: replace-cross Abstract: Large language models can recover mid-generation from task-misaligned activation steering, producing explicit verbal restarts (e.
arXiv Machine Learning
Jun 8
RhinoVLA Technical Report
arXiv:2606. 07383v1 Announce Type: cross Abstract: Vision-Language-Action (VLA) models have shown strong potential for robotic manipulation, but real-time deployment on edge hardware remains challenging.
arXiv Machine Learning
Jun 8
Reactivity-Informed Machine Learning for Performance Prediction and Design Space Exploration of Alkali-Activated Slag
arXiv:2606. 06765v1 Announce Type: cross Abstract: Establishing quantitative relationships among mix design, raw material properties, curing conditions, and performance remains a long-standing challenge in cementitious materials, particularly for alkali-activated materials with variable precursor and activator chemistry.
arXiv AI
Jun 8
ActQuant: Sub-4-bit Action-Guided Quantization for Vision-Language-Action Models
arXiv:2605. 24011v2 Announce Type: replace-cross Abstract: Vision-Language-Action (VLA) models exhibit remarkable action generation for embodied intelligence, but their heavy compute make deployment on edge platforms impractical.
arXiv Machine Learning
Jun 8
GenPO++: Generative Policy Optimization with Jacobian-free Likelihood Ratios
arXiv:2606. 06967v1 Announce Type: new Abstract: Generative policies provide expressive and multimodal action distributions, making them attractive for reinforcement learning (RL) in complex continuous-control tasks.
arXiv AI
Jun 8
MatterDoor: Sampling Zero-shot Spatio-semantic Priors using Generative Models
arXiv:2510. 11014v2 Announce Type: replace-cross Abstract: Autonomous robots often view rooms only partially, through a doorway, where the walls and scene structure hide the geometry and task-relevant semantics needed for safe navigation and goal-directed action.
arXiv Machine Learning
Jun 8
Certified Robustness to Data Poisoning in Gradient-Based Training
arXiv:2406. 05670v3 Announce Type: replace Abstract: Modern machine learning pipelines leverage large amounts of public data, making it infeasible to guarantee data quality and leaving models open to poisoning and backdoor attacks.
arXiv AI
Jun 8
The Sim-to-Real Gap of Foundation Model Agents: A Unified MDP Perspective
arXiv:2606. 07017v1 Announce Type: new Abstract: Foundation model agents are increasingly deployed for real-world decision-making, but suffer from the sim-to-real gap.
arXiv AI
Jun 8
An Abstract Architecture for Explainable Autonomy in Hazardous Environments
arXiv:2606. 07211v1 Announce Type: cross Abstract: Autonomous robotic systems are being proposed for use in hazardous environments, often to reduce the risks to human workers.
arXiv AI
Jun 8
What Matters When Cotraining Robot Manipulation Policies on Everyday Human Videos?
arXiv:2606. 06627v1 Announce Type: cross Abstract: Human video datasets used for cotraining robot manipulation policies largely consist of curated demonstrations where motions are orchestrated to resemble robot behavior and 3D hand poses are captured with specialized hardware.
arXiv AI
Jun 8
EgoPressDiff: Multimodal Video Diffusion for Egocentric UV-Domain Hand-Pressure Estimation
arXiv:2606. 06872v1 Announce Type: cross Abstract: Estimating hand-surface contact pressure from an egocentric view is crucial for AR/VR devices, robotic imitation, and ergonomic analysis.
arXiv AI
Jun 8
Re-imagining ISO 26262 in the Age of Autonomous Vehicles: Enhancing Controllability through Transferability and Predictability
arXiv:2606. 07437v1 Announce Type: cross Abstract: The ISO 26262 standard defines functional safety for road vehicles through risk assessments based on Severity, Exposure, and Controllability, grounded in a human-driven vehicle paradigm.
arXiv AI
Jun 8
Robust Driving Control for Autonomous Vehicles: An Intelligent General-sum Constrained Adversarial Reinforcement Learning Approach
arXiv:2510. 09041v3 Announce Type: replace-cross Abstract: Deep reinforcement learning (DRL) has demonstrated remarkable success in developing autonomous driving policies.
arXiv AI
Jun 8
Chameleon: Control-Indexed Prospective Memory for Visuomotor Manipulation
arXiv:2603. 24576v2 Announce Type: replace-cross Abstract: Robots often observe information that determines a future action long before that action is executed.
arXiv Machine Learning
Jun 8
SERNF: Sample-Efficient Real-World Dexterous Policy Fine-Tuning via Action-Chunked Critics and Normalizing Flows
arXiv:2602. 09580v4 Announce Type: replace-cross Abstract: Real-world fine-tuning of dexterous manipulation policies remains challenging due to limited real-world interaction budgets and highly multimodal action distributions.
arXiv AI
Jun 8
AEGIS: A Backup Reflex for Physical AI
arXiv:2606. 06660v1 Announce Type: new Abstract: Long-horizon robot manipulation tends to fail gradually: one bad step degrades the state, and the policy spirals into a basin from which it cannot recover.
arXiv AI
Jun 8
ScenicRules: An Autonomous Driving Benchmark with Multi-Objective Specifications and Abstract Scenarios
arXiv:2602. 16073v2 Announce Type: replace-cross Abstract: Developing autonomous driving systems for complex traffic environments requires balancing multiple objectives, such as avoiding collisions, obeying traffic rules, and making efficient progress.
arXiv AI
Jun 8
ViVa: A Video-Generative Value Model for Robot Reinforcement Learning
arXiv:2604. 08168v2 Announce Type: replace-cross Abstract: Vision-language-action (VLA) models have advanced robot manipulation through large-scale pretraining, but real-world deployment remains challenging due to partial observability and delayed feedback.
arXiv AI
Jun 8
A Geometric Gaussian Mixture Representation of Plane Curves
arXiv:2606. 06505v1 Announce Type: cross Abstract: We introduce a user defined probabilistic polygonal representation for plane curves.