arXiv Machine Learning
Jul 8
Supervised Reward Inference
arXiv:2502. 18447v2 Announce Type: replace Abstract: Existing approaches to reward inference typically assume that humans provide demonstrations according to specific behavior models.
Robotics and embodied AI
Manipulation, locomotion, sim-to-real transfer and autonomous driving: learning systems that have to survive physics.
arXiv AI
Jul 8
From Passive Observer to Active Critic: Reinforcement Learning Elicits Process Reasoning for Robotic Manipulation
arXiv:2603. 15600v2 Announce Type: replace-cross Abstract: Accurate process supervision remains a critical challenge for long-horizon robotic manipulation.
arXiv Machine Learning
Jul 8
Life Cycle Assessment of Pre-training the Lucie 7B Open-Source Large Language Model on the Jean Zay Supercomputer
arXiv:2607. 05408v1 Announce Type: cross Abstract: The environmental impact of training large language models (LLMs) is increasingly scrutinised, yet most published estimates focus on operational energy and disclose little about manufacturing (embodied) emissions, water consumption, or the underlying highperformance computing (HPC) infrastructure.
arXiv Machine Learning
Jul 8
HERB: Human-augmented Efficient Reinforcement learning for Bin-packing
arXiv:2504. 16595v2 Announce Type: replace-cross Abstract: Packing objects efficiently is a fundamental problem in logistics, warehouse automation, and robotics.
arXiv Machine Learning
Jul 8
Deep Reinforcement Learning for Dynamic Battery Management of Autonomous Order Pickers
arXiv:2607. 05683v1 Announce Type: new Abstract: Battery charging of Autonomous Mobile Robots (AMRs) in warehouses is a critical operational challenge that heavily impacts both order processing times and throughput.
arXiv AI
Jul 8
EcoVision: AI-Powered Drone Imaging for Salt Marsh Vegetation Monitoring and Dominance Mapping
arXiv:2607. 06105v1 Announce Type: cross Abstract: High-resolution RGB imagery acquired from low-altitude UAV surveys was processed through a modular pipeline incorporating transformer-based semantic segmentation, connected-component vegetation extraction, fine-grained species classification using a ConvNeXt architecture, and grid-based dominance scoring at 2x2m resolution.
arXiv Machine Learning
Jul 8
PoseVLA: Universal Pose Pretraining for Generalizable Vision-Language-Action Policies
arXiv:2602. 19710v3 Announce Type: replace-cross Abstract: Existing Vision-Language-Action (VLA) models often suffer from feature collapse and low training efficiency because they entangle high-level perception with sparse, embodiment-specific action supervision.
arXiv AI
Jul 8
Onnes: A Physics-Grounded Multi-Agent LLM Simulator for Cryogenic Fault Diagnosis in Quantum Computing Infrastructure
arXiv:2607. 05805v1 Announce Type: new Abstract: Dilution refrigerators are the enabling infrastructure of superconducting quantum computers, yet their fault diagnosis is still dominated by threshold alarms that report that something is wrong, not what.
arXiv AI
Jul 8
A Definition and Roadmap for World Models
arXiv:2607. 06401v1 Announce Type: new Abstract: World models -- internal simulators that learn the structure and dynamics of an environment -- have become one of the most actively debated concepts in AI.
arXiv AI
Jul 8
Harnessing Generative Image Models for Training-Free Primitive Shape Abstraction
arXiv:2607. 05568v1 Announce Type: cross Abstract: Representing 3D shapes as compact sets of geometric primitives is fundamental to robotics, simulation, and scene understanding.
arXiv AI
Jul 8
CSTutorBench: Benchmarking Small Language Models as Tutors for Block-Based Programming
arXiv:2607. 05571v1 Announce Type: new Abstract: Large language models are increasingly explored as AI tutors, yet deploying them in K-12 settings raises concerns around privacy, cost, and reliance on proprietary models.
arXiv Machine Learning
Jul 8
A Comparative Study of EMG- and IMU-based Gesture Recognition at the Wrist and Forearm
arXiv:2512. 07997v2 Announce Type: replace-cross Abstract: Gestures are an integral part of our daily interactions with the environment.
arXiv AI
Jul 8
Driving the Wrong Way: Leveraging Interpretability in End2End Autonomous Driving Models
arXiv:2607. 06328v1 Announce Type: new Abstract: The increasing adoption of end-to-end learning for autonomous driving introduces increased model complexity and opacity, raising the risk of learning undesired or erroneous behavior.
arXiv AI
Jul 8
CanvasAgent: Enabling Complex Image Creation and Editing via Visual Tool Orchestration
arXiv:2607. 05465v1 Announce Type: cross Abstract: Complex image creation and editing often require more than a single generation or editing model.
Hugging Face Trending Papers
Jul 8
Dynamic Object Detection and Tracking in Construction: A Fisheye Camera and LiDAR Sensor Fusion Model
Robust dynamic object detection and tracking are essential for enabling robots to operate safely and effectively alongside humans in complex environments such as construction sites. While LiDAR-based SLAM and occupancy grid methods offer viable solutions for detecting and tracking motion, many state-of-the-art 3D vision approaches rely heavily on pre-trained neural networks and require additional post-processing to identify moving objects.
Hugging Face Trending Papers
Jul 8
GemNav: Discrete-Token Visual Robot Navigation using a Multimodal Large Language Model
Visual navigation policies built on large pretrained models have so far followed a common recipe: a dedicated visual encoder, a bespoke action head, and training on thousands of hours of cross-embodiment datasets. We ask whether this recipe is necessary.
Hugging Face Trending Papers
Jul 7
SPEAR: A Simulator for Photorealistic Embodied AI Research
Interactive simulators have become powerful tools for training embodied agents and generating synthetic visual data, but existing photorealistic simulators suffer from limited generality, programmability, and rendering speed. We address these limitations by introducing SPEAR: A Simulator for Photorealistic Embodied AI Research.
Hugging Face Trending Papers
Jul 7
WristMimic: Full-Body Humanoid Control with Wrist-Guided Manipulation
Retargeting human object interaction demonstrations to physics based simulation requires reproducing not only body motion but also the object motion and contacts that make manipulation succeed. However, position only hand trajectories do not specify the contact forces needed to manipulate objects, and directly tracking them can overconstrain contact rich finger behavior.
Hugging Face Trending Papers
Jul 7
A Definition and Roadmap for World Models
World models -- internal simulators that learn the structure and dynamics of an environment -- have become one of the most actively debated concepts in AI. From model-based reinforcement learning and video generation to embodied robotics and ultimately, physical AI, researchers across AI subfields are building systems that they call "world models", yet there is no consensus on what a world model fundamentally is, what it should predict, or how it should be built.
Hugging Face Trending Papers
Jul 7
Training-Free Acceleration for Vision-Language-Action Models with Action Caching and Refinement
Vision-Language-Action (VLA) models have emerged as a promising approach for generalizable robotic manipulations. In particular, flow matching-based VLA models have shown remarkable success due to their capability to generate precise and smooth action sequences and capture multimodal distributions.