Physical AI, robots, and autonomous systems
The company turns footage from robots into structured, searchable datasets with a deep learning model.
Everyone talks about AI models, but the real bottleneck might be hardware. According to a recent study by Roots Analysis: AI chip market ...
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? ...
![[2602.00851] Persuasion Propagation in LLM Agents](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
The paper explores how user persuasion affects the behavior of large language model (LLM) agents during long-horizon tasks, revealing tha...
This paper presents a probabilistic method to measure the representativeness of scenario suites for autonomous systems, focusing on ensur...
The article presents Dataforge, an LLM-powered platform designed to automate data engineering processes, enhancing efficiency in preparin...
ParaCook introduces a benchmark for time-efficient planning in multi-agent systems, focusing on collaborative tasks inspired by cooking g...
This paper introduces a novel approach using the Cramér-von Mises statistic to create incentive mechanisms that promote truthful data sha...
This article evaluates the persuasive capabilities of frontier large language models (LLMs) on harmful topics, introducing a new benchmar...
The paper introduces PhyScensis, a framework that uses physics-augmented LLM agents to generate complex 3D physical scenes for robotic ma...
ManeuverNet introduces a Soft Actor-Critic framework for enhancing the maneuverability of double-Ackermann-steering robots, addressing li...
The paper presents Big Picture Policies (BPP), a novel approach to robot imitation learning that enhances performance by focusing on key ...
ThermEval introduces a benchmark for evaluating vision-language models on thermal imagery, highlighting their limitations in temperature-...
This paper presents a machine learning-assisted framework for optimizing ship hull designs using adjoint-based methods, addressing challe...
The paper discusses a governance architecture for autonomous agents, focusing on bounding decision authority to ensure safety in high-sta...
This article presents a comprehensive study on the vulnerability of open-weight models to prefill attacks, revealing significant security...
This paper presents a Bayesian approach to low-discrepancy subset selection, addressing its NP-hardness and proposing a Bayesian Optimiza...
The paper presents TWISTED-RL, a novel framework for robotic knot-tying that enhances performance without human demonstrations by utilizi...
The paper discusses a novel system for autonomous book ideation using synthetic reader panels composed of LLM personas to evaluate book c...
The paper presents pFedNavi, a personalized federated learning framework for Vision-Language Navigation (VLN) that addresses privacy conc...
This article presents a two-stage reinforcement learning approach to enhance the performance of quadruped robots in climbing U-shaped sta...
This article presents a trajectory-based safety audit of Clawdbot, an AI agent, evaluating its performance across various risk dimensions...
The paper presents AdaptManip, an autonomous framework for humanoid robots to perform object lifting and delivery using reinforcement lea...
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