Robotics & Embodied AI

Physical AI, robots, and autonomous systems

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[2512.16705] Olaf: Bringing an Animated Character to Life in the Physical World
Robotics

[2512.16705] Olaf: Bringing an Animated Character to Life in the Physical World

Abstract page for arXiv paper 2512.16705: Olaf: Bringing an Animated Character to Life in the Physical World

arXiv - Machine Learning · 4 min ·
[2510.13714] DeDelayed: Deleting Remote Inference Delay via On-Device Correction
Machine Learning

[2510.13714] DeDelayed: Deleting Remote Inference Delay via On-Device Correction

Abstract page for arXiv paper 2510.13714: DeDelayed: Deleting Remote Inference Delay via On-Device Correction

arXiv - Machine Learning · 4 min ·
[2604.02226] When to ASK: Uncertainty-Gated Language Assistance for Reinforcement Learning
Llms

[2604.02226] When to ASK: Uncertainty-Gated Language Assistance for Reinforcement Learning

Abstract page for arXiv paper 2604.02226: When to ASK: Uncertainty-Gated Language Assistance for Reinforcement Learning

arXiv - Machine Learning · 3 min ·

All Content

[2602.12487] Gradient-Enhanced Partitioned Gaussian Processes for Real-Time Quadrotor Dynamics Modeling
Machine Learning

[2602.12487] Gradient-Enhanced Partitioned Gaussian Processes for Real-Time Quadrotor Dynamics Modeling

This paper introduces a novel Gaussian Process model for quadrotor dynamics that integrates gradient information, enabling real-time infe...

arXiv - Machine Learning · 4 min ·
[2602.12407] MiDAS: A Multimodal Data Acquisition System and Dataset for Robot-Assisted Minimally Invasive Surgery
Robotics

[2602.12407] MiDAS: A Multimodal Data Acquisition System and Dataset for Robot-Assisted Minimally Invasive Surgery

The paper presents MiDAS, an open-source multimodal data acquisition system for robot-assisted minimally invasive surgery, enabling synch...

arXiv - Machine Learning · 3 min ·
[2602.12405] Self-Refining Vision Language Model for Robotic Failure Detection and Reasoning
Llms

[2602.12405] Self-Refining Vision Language Model for Robotic Failure Detection and Reasoning

The paper presents ARMOR, a self-refining vision language model designed for robotic failure detection and reasoning, achieving significa...

arXiv - Machine Learning · 4 min ·
[2602.13052] Quantization-Aware Collaborative Inference for Large Embodied AI Models
Machine Learning

[2602.13052] Quantization-Aware Collaborative Inference for Large Embodied AI Models

This paper explores quantization-aware collaborative inference for large embodied AI models, addressing challenges in resource-limited en...

arXiv - Machine Learning · 3 min ·
[2602.13040] TCRL: Temporal-Coupled Adversarial Training for Robust Constrained Reinforcement Learning in Worst-Case Scenarios
Machine Learning

[2602.13040] TCRL: Temporal-Coupled Adversarial Training for Robust Constrained Reinforcement Learning in Worst-Case Scenarios

The paper presents TCRL, a novel framework for robust constrained reinforcement learning that addresses challenges posed by temporally co...

arXiv - Machine Learning · 4 min ·
[2602.12636] Dual-Granularity Contrastive Reward via Generated Episodic Guidance for Efficient Embodied RL
Machine Learning

[2602.12636] Dual-Granularity Contrastive Reward via Generated Episodic Guidance for Efficient Embodied RL

This paper introduces the Dual-Granularity Contrastive Reward framework, which enhances sample efficiency in reinforcement learning (RL) ...

arXiv - Machine Learning · 4 min ·
[2602.12520] Multi-Agent Model-Based Reinforcement Learning with Joint State-Action Learned Embeddings
Machine Learning

[2602.12520] Multi-Agent Model-Based Reinforcement Learning with Joint State-Action Learned Embeddings

This paper presents a novel framework for multi-agent model-based reinforcement learning, integrating joint state-action representation l...

arXiv - Machine Learning · 3 min ·
[2602.10915] Blind Gods and Broken Screens: Architecting a Secure, Intent-Centric Mobile Agent Operating System
Llms

[2602.10915] Blind Gods and Broken Screens: Architecting a Secure, Intent-Centric Mobile Agent Operating System

The paper presents Aura, a secure mobile agent operating system designed to address vulnerabilities in current app-centric models by impl...

arXiv - AI · 4 min ·
[2602.10234] Transforming Policy-Car Swerving for Mitigating Stop-and-Go Traffic Waves: A Practice-Oriented Jam-Absorption Driving Strategy
Ai Agents

[2602.10234] Transforming Policy-Car Swerving for Mitigating Stop-and-Go Traffic Waves: A Practice-Oriented Jam-Absorption Driving Strategy

This article presents a novel driving strategy to mitigate stop-and-go traffic waves using a jam-absorption technique inspired by police-...

arXiv - AI · 4 min ·
[2602.08543] GISA: A Benchmark for General Information-Seeking Assistant
Llms

[2602.08543] GISA: A Benchmark for General Information-Seeking Assistant

The paper introduces GISA, a benchmark designed for evaluating General Information-Seeking Assistants, addressing limitations in existing...

arXiv - AI · 4 min ·
[2601.09605] Sim2real Image Translation Enables Viewpoint-Robust Policies from Fixed-Camera Datasets
Nlp

[2601.09605] Sim2real Image Translation Enables Viewpoint-Robust Policies from Fixed-Camera Datasets

The paper presents MANGO, a novel image translation method that enhances viewpoint robustness in robot manipulation policies using fixed-...

arXiv - AI · 4 min ·
[2508.05004] R-Zero: Self-Evolving Reasoning LLM from Zero Data
Llms

[2508.05004] R-Zero: Self-Evolving Reasoning LLM from Zero Data

The article presents R-Zero, a self-evolving reasoning LLM that autonomously generates training data, improving AI capabilities without h...

arXiv - Machine Learning · 4 min ·
[2507.12108] Multimodal Coordinated Online Behavior: Trade-offs and Strategies
Robotics

[2507.12108] Multimodal Coordinated Online Behavior: Trade-offs and Strategies

This paper explores multimodal coordinated online behavior, analyzing trade-offs between different integration strategies and their effec...

arXiv - Machine Learning · 4 min ·
[2503.22809] Data-Driven Worker Activity Recognition and Efficiency Estimation in Manual Fruit Harvesting
Machine Learning

[2503.22809] Data-Driven Worker Activity Recognition and Efficiency Estimation in Manual Fruit Harvesting

This study presents a data-driven system for recognizing worker activities and estimating efficiency in manual fruit harvesting, specific...

arXiv - Machine Learning · 4 min ·
[2510.23883] Agentic AI Security: Threats, Defenses, Evaluation, and Open Challenges
Llms

[2510.23883] Agentic AI Security: Threats, Defenses, Evaluation, and Open Challenges

This article explores the security implications of agentic AI systems, detailing specific threats, defense strategies, and evaluation met...

arXiv - AI · 3 min ·
[2510.07117] The Conditions of Physical Embodiment Enable Generalization and Care
Ai Agents

[2510.07117] The Conditions of Physical Embodiment Enable Generalization and Care

This paper explores how physical embodiment in artificial agents can enhance their ability to generalize and provide care in uncertain en...

arXiv - Machine Learning · 4 min ·
[2602.13156] In-Context Autonomous Network Incident Response: An End-to-End Large Language Model Agent Approach
Llms

[2602.13156] In-Context Autonomous Network Incident Response: An End-to-End Large Language Model Agent Approach

This article presents a novel approach to network incident response using a large language model (LLM) that autonomously learns and adapt...

arXiv - AI · 4 min ·
[2602.13071] Bus-Conditioned Zero-Shot Trajectory Generation via Task Arithmetic
Machine Learning

[2602.13071] Bus-Conditioned Zero-Shot Trajectory Generation via Task Arithmetic

This paper introduces MobTA, a novel approach for generating mobility trajectories without requiring real data from the target city, usin...

arXiv - Machine Learning · 4 min ·
[2602.13061] Diverging Flows: Detecting Extrapolations in Conditional Generation
Machine Learning

[2602.13061] Diverging Flows: Detecting Extrapolations in Conditional Generation

The paper introduces Diverging Flows, a method for detecting extrapolations in conditional generation models, enhancing safety in applica...

arXiv - Machine Learning · 3 min ·
[2602.12983] Detecting Object Tracking Failure via Sequential Hypothesis Testing
Machine Learning

[2602.12983] Detecting Object Tracking Failure via Sequential Hypothesis Testing

This paper presents a method for detecting object tracking failures using sequential hypothesis testing, enhancing safety in computer vis...

arXiv - AI · 4 min ·
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Machine Learning Large Language Models Generative AI Natural Language Processing Computer Vision AI Safety & Ethics

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