Physical AI, robots, and autonomous systems
I've been sitting with a question for a while: what happens when AI agents aren't just tools to be used, but participants in an economy? ...
Some insight onto building a muilti agent autonomous system. This is like the daily newspaper for the project. A quick read to see how ou...
![[2603.13846] Is Seeing Believing? Evaluating Human Sensitivity to Synthetic Video](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Abstract page for arXiv paper 2603.13846: Is Seeing Believing? Evaluating Human Sensitivity to Synthetic Video
The paper discusses a method for embodied AI agents to infer user goals from open-ended dialogues using Large Language Models (LLMs), emp...
The paper presents FAMOSE, a novel framework that utilizes the ReAct paradigm for automated feature discovery in machine learning, enhanc...
This paper presents Deep-Flow, an innovative framework for anomaly detection in autonomous driving, utilizing Optimal Transport Condition...
This paper outlines a vision for fully autonomous, AI-native particle accelerators, emphasizing AI co-design for optimal performance and ...
This article provides a comprehensive overview of optical remote sensing, highlighting advancements in computer vision and drone technolo...
The paper presents SIREN, an AI framework for enhancing UAV-assisted emergency networks by converting voice communications into structure...
This paper explores vulnerabilities in embodied AI systems, highlighting the inadequacy of existing analyses focused solely on LLMs or CP...
The paper presents a novel framework for continual uncertainty learning in robust control of nonlinear dynamical systems, addressing chal...
This paper presents a novel approach to 3D scene rendering using multimodal Gaussian splatting, integrating RF sensing for improved accur...
The paper presents 'Wink', a system designed to recover coding agents from misbehaviors, enhancing their reliability in software developm...
The paper presents MALLVI, a multi-agent framework for robotic manipulation that utilizes closed-loop feedback to enhance task planning a...
SimToolReal presents a novel approach to zero-shot dexterous tool manipulation using an object-centric policy, enhancing robotic capabili...
This study investigates whether adversarial code comments can mislead AI security reviewers during vulnerability detection in code, revea...
AutoNumerics is a multi-agent framework that autonomously designs and verifies numerical solvers for PDEs from natural language, outperfo...
The paper explores the evolution of 6G wireless communication, emphasizing the shift towards intent-aware, autonomous systems that adapt ...
This study analyzes how AI coding agents create pull request descriptions and how human reviewers respond, revealing distinct styles and ...
The paper presents IntentCUA, a framework for multi-agent planning in computer-use agents, focusing on intent-level representations to en...
This paper presents Phantom, an automated framework for agent hijacking via Structural Template Injection, enhancing attack success rates...
The paper presents Mobile-Agent-v3.5, a multi-platform GUI agent model, showcasing its advanced capabilities in GUI automation and real-t...
The article discusses the integration of artificial intelligence in the manufacturing of rocket parts, highlighting its potential to enha...
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