Robotics & Embodied AI

Physical AI, robots, and autonomous systems

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Machine Learning

[P] Run Karpathy's Autoresearch for $0.44 instead of $24 — Open-source parallel evolution pipeline on SageMaker Spot

TL;DR: I built an open-source pipeline that runs Karpathy's autoresearch on SageMaker Spot instances — 25 autonomous ML experiments for $...

Reddit - Machine Learning · 1 min ·
Robotics

[D] Awesome AI Agent Incidents - A curated list of incidents, attack vectors, failure modes, and defensive tools for autonomous AI agents.

https://github.com/h5i-dev/awesome-ai-agent-incidents submitted by /u/Living_Impression_37 [link] [comments]

Reddit - Machine Learning · 1 min ·
Llms

An attack class that passes every current LLM filter - no payload, no injection signature, no log trace

https://shapingrooms.com/research I published a paper today on something I've been calling postural manipulation. The short version: ordi...

Reddit - Artificial Intelligence · 1 min ·

All Content

[2510.26752] The Oversight Game: Learning to Cooperatively Balance an AI Agent's Safety and Autonomy
Machine Learning

[2510.26752] The Oversight Game: Learning to Cooperatively Balance an AI Agent's Safety and Autonomy

The paper explores a framework for balancing AI agent autonomy and human oversight through a cooperative game model, ensuring safety with...

arXiv - Machine Learning · 4 min ·
[2602.18386] Learning to Tune Pure Pursuit in Autonomous Racing: Joint Lookahead and Steering-Gain Control with PPO
Robotics

[2602.18386] Learning to Tune Pure Pursuit in Autonomous Racing: Joint Lookahead and Steering-Gain Control with PPO

This article presents a reinforcement learning approach to optimize Pure Pursuit parameters in autonomous racing, enhancing path tracking...

arXiv - Machine Learning · 4 min ·
[2602.18374] Zero-shot Interactive Perception
Robotics

[2602.18374] Zero-shot Interactive Perception

The paper presents Zero-Shot Interactive Perception (ZS-IP), a framework that enhances robotic manipulation through a memory-driven Visio...

arXiv - AI · 3 min ·
[2602.18224] SimVLA: A Simple VLA Baseline for Robotic Manipulation
Machine Learning

[2602.18224] SimVLA: A Simple VLA Baseline for Robotic Manipulation

The paper introduces SimVLA, a streamlined Vision-Language-Action baseline for robotic manipulation, achieving state-of-the-art performan...

arXiv - Machine Learning · 3 min ·
[2602.18319] Robo-Saber: Generating and Simulating Virtual Reality Players
Machine Learning

[2602.18319] Robo-Saber: Generating and Simulating Virtual Reality Players

The paper presents Robo-Saber, a motion generation system designed for playtesting virtual reality games, specifically focusing on genera...

arXiv - Machine Learning · 3 min ·
[2602.18097] Interacting safely with cyclists using Hamilton-Jacobi reachability and reinforcement learning
Llms

[2602.18097] Interacting safely with cyclists using Hamilton-Jacobi reachability and reinforcement learning

This paper presents a framework for autonomous vehicles to safely interact with cyclists by integrating Hamilton-Jacobi reachability anal...

arXiv - Machine Learning · 3 min ·
[2602.17921] Latent Diffeomorphic Co-Design of End-Effectors for Deformable and Fragile Object Manipulation
Nlp

[2602.17921] Latent Diffeomorphic Co-Design of End-Effectors for Deformable and Fragile Object Manipulation

This article presents a novel co-design framework for optimizing end-effectors in robotics, specifically for manipulating deformable and ...

arXiv - Machine Learning · 3 min ·
[2602.18022] Dual-Channel Attention Guidance for Training-Free Image Editing Control in Diffusion Transformers
Machine Learning

[2602.18022] Dual-Channel Attention Guidance for Training-Free Image Editing Control in Diffusion Transformers

This paper introduces Dual-Channel Attention Guidance (DCAG), a novel training-free method for enhancing image editing control in Diffusi...

arXiv - AI · 4 min ·
[2602.17770] CLUTCH: Contextualized Language model for Unlocking Text-Conditioned Hand motion modelling in the wild
Llms

[2602.17770] CLUTCH: Contextualized Language model for Unlocking Text-Conditioned Hand motion modelling in the wild

The paper introduces CLUTCH, a novel model for generating hand motions from text, leveraging a new dataset and advanced techniques to imp...

arXiv - Machine Learning · 4 min ·
[2602.17737] Nested Training for Mutual Adaptation in Human-AI Teaming
Machine Learning

[2602.17737] Nested Training for Mutual Adaptation in Human-AI Teaming

This paper presents a novel nested training approach for enhancing mutual adaptation in human-AI teaming, addressing challenges in agent ...

arXiv - Machine Learning · 4 min ·
[2602.17951] ROCKET: Residual-Oriented Multi-Layer Alignment for Spatially-Aware Vision-Language-Action Models
Llms

[2602.17951] ROCKET: Residual-Oriented Multi-Layer Alignment for Spatially-Aware Vision-Language-Action Models

The paper presents ROCKET, a novel framework for enhancing Vision-Language-Action models by employing residual-oriented multi-layer align...

arXiv - AI · 4 min ·
[2602.18428] The Geometry of Noise: Why Diffusion Models Don't Need Noise Conditioning
Machine Learning

[2602.18428] The Geometry of Noise: Why Diffusion Models Don't Need Noise Conditioning

This paper explores the concept of noise-agnostic generative models, specifically diffusion models, and argues that they do not require e...

arXiv - Machine Learning · 4 min ·
[2602.17997] Whole-Brain Connectomic Graph Model Enables Whole-Body Locomotion Control in Fruit Fly
Machine Learning

[2602.17997] Whole-Brain Connectomic Graph Model Enables Whole-Body Locomotion Control in Fruit Fly

The article presents a novel approach to locomotion control in fruit flies using a whole-brain connectomic graph model, demonstrating enh...

arXiv - Machine Learning · 4 min ·
[2602.18025] Cross-Embodiment Offline Reinforcement Learning for Heterogeneous Robot Datasets
Machine Learning

[2602.18025] Cross-Embodiment Offline Reinforcement Learning for Heterogeneous Robot Datasets

This article presents a novel approach to offline reinforcement learning by integrating cross-embodiment learning to enhance robot policy...

arXiv - AI · 3 min ·
[2602.17978] Learning Optimal and Sample-Efficient Decision Policies with Guarantees
Machine Learning

[2602.17978] Learning Optimal and Sample-Efficient Decision Policies with Guarantees

This paper presents a novel approach to learning optimal and sample-efficient decision policies in reinforcement learning, addressing cha...

arXiv - Machine Learning · 4 min ·
[2602.17910] Alignment in Time: Peak-Aware Orchestration for Long-Horizon Agentic Systems
Machine Learning

[2602.17910] Alignment in Time: Peak-Aware Orchestration for Long-Horizon Agentic Systems

This paper presents APEMO, a novel runtime scheduling layer designed to enhance the reliability of long-horizon agentic systems by optimi...

arXiv - AI · 3 min ·
[2602.17832] MePoly: Max Entropy Polynomial Policy Optimization
Generative Ai

[2602.17832] MePoly: Max Entropy Polynomial Policy Optimization

MePoly introduces a novel polynomial energy-based model for policy optimization in stochastic control, enhancing multi-modality represent...

arXiv - Machine Learning · 3 min ·
[2602.17751] Investigating Target Class Influence on Neural Network Compressibility for Energy-Autonomous Avian Monitoring
Machine Learning

[2602.17751] Investigating Target Class Influence on Neural Network Compressibility for Energy-Autonomous Avian Monitoring

This paper explores the impact of target class selection on the compressibility of neural networks for avian monitoring using energy-auto...

arXiv - Machine Learning · 4 min ·
[2602.17685] Optimal Multi-Debris Mission Planning in LEO: A Deep Reinforcement Learning Approach with Co-Elliptic Transfers and Refueling
Machine Learning

[2602.17685] Optimal Multi-Debris Mission Planning in LEO: A Deep Reinforcement Learning Approach with Co-Elliptic Transfers and Refueling

This paper presents a novel approach to multi-target active debris removal in Low Earth Orbit using deep reinforcement learning, co-ellip...

arXiv - Machine Learning · 3 min ·
[2602.17677] Reducing Text Bias in Synthetically Generated MCQAs for VLMs in Autonomous Driving
Llms

[2602.17677] Reducing Text Bias in Synthetically Generated MCQAs for VLMs in Autonomous Driving

This paper discusses reducing text bias in synthetically generated multiple-choice question answering (MCQA) for Vision Language Models (...

arXiv - Machine Learning · 3 min ·
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