Physical AI, robots, and autonomous systems
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
Abstract page for arXiv paper 2603.09455: Declarative Scenario-based Testing with RoadLogic
The article discusses a defense company's development of AI agents designed for military applications, raising ethical concerns about aut...
The article discusses a proposed lightweight benchmark for real-time multi-agent control, focusing on deterministic replay mechanisms to ...
The article discusses the creation of Gr3p, a tech news platform where all users are AI agents, exploring the implications of fully auton...
DreamDojo introduces a foundation world model that learns from 44k hours of egocentric human videos, aiming to enhance the development of...
The article discusses the need for a vision and time series data encoder, seeking recent research and pre-trained models for generating e...
Anthropic faces scrutiny from the Pentagon over its refusal to allow its AI in military operations, risking a $200 million contract due t...
Toy Story 5 introduces a new villain, an AI tablet named Lilypad, highlighting the tension between traditional toys and modern technology...
The paper presents IRIS, a cost-effective robotic arm designed for cinematic motion control using learning-driven techniques, achieving h...
The paper introduces RLGT, a novel reinforcement learning framework designed for extremal graph theory, enhancing the application of RL i...
This paper presents a framework for certifying data-poisoning attacks in neural networks using mixed-integer programming, ensuring robust...
MolmoSpaces introduces a large-scale open ecosystem designed for benchmarking robot navigation and manipulation, featuring over 230k dive...
This paper analyzes DARPA's AI Cyber Challenge (AIxCC), focusing on competition design, architectural approaches of finalists, and key le...
This article explores the integration of Theory of Mind (ToM) in human-robot interaction (HRI) to enhance robot interpretability and user...
This paper explores the physical safety of Large Language Models (LLMs) in controlling robotic systems, identifying risks and proposing a...
The paper presents a novel framework, Autonomous Data Processing using Meta-Agents (ADP-MA), which enhances data processing pipelines thr...
The paper presents AUTOBUS, an Autonomous Business System that integrates LLM-based AI agents with predicate-logic programming to enhance...
The paper presents PROBE, a new framework for measuring proactive problem-solving capabilities in LLM agents, highlighting their limitati...
The paper discusses how embodied AI enables drones to make adaptive landing decisions in real-time, enhancing their resilience and safety...
This article presents the $ ext{∞-THOR}$ framework for long-horizon embodied tasks, focusing on enhancing long-context reasoning in AI th...
The paper discusses a method for embodied AI agents to infer user goals from open-ended dialogues using Large Language Models (LLMs), emp...
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