arXiv AI
Jul 31
From Passive Video to Editable Experience: Physically Grounded Experience Synthesis for Embodied Intelligence
arXiv:2607. 26903v1 Announce Type: new Abstract: The key bottleneck in embodied AI is not model architecture but data.
Robotics and embodied AI
Manipulation, locomotion, sim-to-real transfer and autonomous driving: learning systems that have to survive physics.
arXiv AI
Jul 31
Reinforcement Learning on Cost-Constrained Quadrupedal Hardware
arXiv:2607. 26434v2 Announce Type: cross Abstract: Deploying learned control policies on low-cost robotic platforms introduces transport latencies and noisy motor feedback that systematically widens the sim-to-real gap.
arXiv Machine Learning
Jul 31
Cross-Embodiment Transfer via Behavior-Aligned Representations
arXiv:2607. 27549v1 Announce Type: cross Abstract: Recent progress in large-scale imitation learning for robot manipulation has been driven by leveraging datasets across a wide range of robot embodiments.
arXiv Machine Learning
Jul 31
QuantWAMs: Calibrating at the Right Granularity for World Action Models
arXiv:2607. 28405v1 Announce Type: cross Abstract: World Action Models (WAMs) jointly predict future observations and actions, but their iterative denoising and closed-loop execution make efficient deployment costly.
arXiv AI
Jul 31
CG-World: A Large-Scale World-State Dataset and Protocol for World Models
arXiv:2607. 26452v1 Announce Type: new Abstract: World models must learn the joint dynamics of states, actions, events, and observations, yet existing video, robotics, and simulation datasets usually capture only part of this structure.
arXiv Machine Learning
Jul 31
Filling the Pareto-Optimal Front for Affordance Segmentation on Embedded Devices Using RGB-D Cameras
arXiv:2607. 28293v1 Announce Type: cross Abstract: While depth sensors have the potential to complement RGB data for affordance segmentation in wearable robots, their usage seems to remain underexplored.
arXiv AI
Jul 31
Physically Real-time Infrared Attack against Optical Flow Estimation Networks
arXiv:2607. 26651v1 Announce Type: cross Abstract: With the promising performance of deep neural networks on image-based tasks, different real-world applications such as autonomous driving and motion detection have become increasingly mature and relevant to human lives.
arXiv AI
Jul 31
A Methodology for Designing Knowledge-Driven Missions for Robots
arXiv:2601. 20797v1 Announce Type: cross Abstract: This paper presents a comprehensive methodology for implementing knowledge graphs in ROS 2 systems, aiming to enhance the efficiency and intelligence of autonomous robotic missions.
arXiv Machine Learning
Jul 31
Good Rankers, Bad Objectives: Bilinear Contrastive Critics under Expressive Policy Search
arXiv:2607. 27422v1 Announce Type: new Abstract: Good action rankings do not make a contrastive critic safe to maximize.
arXiv AI
Jul 31
Task and Skill Planning: Hierarchical Robot Planning with Black-Box Skills
arXiv:2504. 17901v3 Announce Type: replace-cross Abstract: Task and motion planning (TAMP) is a well-established approach for solving long-horizon robot planning problems.
arXiv AI
Jul 31
Balancing Centralized Learning and Distributed Self-Organization: A Hybrid Model for Embodied Morphogenesis
arXiv:2511. 10101v2 Announce Type: replace Abstract: Background: both embodied intelligence and developmental morphogenesis depend on a division of labour between centralized guidance and distributed material dynamics, but the amount of top-down control needed to steer self-organization remains unclear.
arXiv AI
Jul 31
BioVLN: A Simulation Platform for Visual Language Navigation in Biomedical Laboratories
arXiv:2607. 26914v1 Announce Type: cross Abstract: Biomedical laboratory robots must navigate to instruments before performing experimental procedures.
arXiv AI
Jul 31
Filesystem-Based Memory for LLM Agents: Organization, Evolution, and Sustainability
arXiv:2607. 26637v1 Announce Type: cross Abstract: Deployed LLM agents increasingly keep their long-term memory as a filesystem: a directory tree of markdown files that the agent itself reads, writes, and reorganizes through generic file tools.
arXiv AI
Jul 31
PUDA: An AI-Native Hardware Harness for Self-Driving Laboratories
arXiv:2607. 26464v1 Announce Type: cross Abstract: Physical Unified Device Architecture (PUDA) is an AI-native hardware harness for self-driving laboratories (SDLs).
arXiv Machine Learning
Jul 31
EMBL AI Librarian: Life-Sciences Knowledge Layer for AI Agents
arXiv:2607. 28229v1 Announce Type: cross Abstract: The web is increasingly accessed by AI agents rather than humans.
arXiv AI
Jul 31
What Does It Take to Detect an AI Agent? Minimal Feature Sets for Behavioral Detection under Browser Automation
arXiv:2607. 26935v1 Announce Type: new Abstract: Bot detectors deployed at scale treat traffic as binary: human or bot.
arXiv AI
Jul 31
TraceCoder: Explainable and Auditable Code Generation with Position-Key Snippet Versioning
arXiv:2607. 26307v1 Announce Type: new Abstract: Contemporary LLM-based coding agents produce code as black-box outputs: the rationale behind each line is hidden, the evolution of the code through benchmark-driven repair is ephemeral, and post-hoc auditing is impossible.
arXiv AI
Jul 31
The Reliability of LLMs for Medical Diagnosis: An Examination of Consistency, Manipulation, and Contextual Awareness
arXiv:2503. 10647v2 Announce Type: replace-cross Abstract: This study evaluated the diagnostic reliability of two Large Language Models (LLMs), Google Gemini 2.
DeepMind Blog
Jul 30
Gemini Robotics ER 2: powering robotics with video understanding, task orchestration, and multi-robot collaboration
Gemini Robotics ER 2 helps robots reason, collaborate, and solve real-world tasks. It represents a step change in video understanding, tool orchestration, and multi-robot collaboration for robotic applications.
Hugging Face Trending Papers
Jul 30
Security of World-Model-Based Embodied AI: A Lifecycle of Threats, Defenses, and Evaluation
World models give embodied AI a predictive core: they compress observations into states, simulate action-conditioned futures, and enable planning beyond reactive control. This predictive layer, however, opens a new security boundary-compromise can propagate from data, sensors, prompts, or feedback into physical action.