Autonomous agents, tool use, and agentic systems
so a while back me and a few folks started working on Caliber, an open source tool for managing AI agent configs and syncing them with yo...
Wandb CLI and MCP is atrocious to use with agents for full autonomous research loops. They are slow, clunky, and result in context rot. S...
Wandb CLI and MCP is atrocious to use with agents for full autonomous research loops. They are slow, clunky, and result in context rot. S...
![[2602.20057] AdaWorldPolicy: World-Model-Driven Diffusion Policy with Online Adaptive Learning for Robotic Manipulation](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
The paper presents AdaWorldPolicy, a novel framework for robotic manipulation that utilizes world models and online adaptive learning to ...
This article explores the relationship between loss flatness and compressed neural representations, introducing new measures and empirica...
This paper presents a novel constraint-based planning framework for mobile robots, enabling zero-shot generalization in interactive navig...
The paper introduces the Very Big Video Reasoning (VBVR) Dataset, a large-scale resource for studying video reasoning capabilities, featu...
AgenticSum presents a novel framework for improving clinical text summarization using large language models, focusing on reducing factual...
The paper introduces SkillInject, a benchmark for evaluating the vulnerability of LLM agents to skill file attacks, revealing high suscep...
The paper presents ReAttn, a novel strategy to enhance attention-based re-ranking in large language models by reducing lexical bias and i...
The paper presents the Descent-Guided Policy Gradient (DG-PG) method, which enhances cooperative multi-agent reinforcement learning by re...
The paper presents MaSoN, an innovative framework for unsupervised change detection in remote sensing that generates diverse changes in l...
The paper presents GOAL, a framework for Continual Generalized Category Discovery (C-GCD) that enhances class discovery while minimizing ...
This article presents a Normal Behavior Model (NBM) for forecasting monitoring data from the ASTRI-Horn telescope, demonstrating effectiv...
The paper presents MAS-FIRE, a framework for evaluating the reliability of LLM-based Multi-Agent Systems through fault injection, address...
The paper presents Janus-Q, an innovative framework for event-driven trading that leverages financial news events as primary decision-mak...
The paper presents Depth-Structured Music Recurrence (DSMR), a novel approach for symbolic music modeling that optimizes long-context pro...
DReX is a novel multimodal recommendation framework that enhances user and item representation through explainable deep learning, address...
The paper presents a novel approach to exact discrete stochastic simulation using deep-learning-scale gradient optimization, enhancing sc...
This article presents a proof-of-concept system for automating iconographic classification and content-based recommendations for digitize...
TeHOR introduces a novel framework for 3D human and object reconstruction using text descriptions, addressing limitations in current meth...
This article presents a novel approach for continuous telemonitoring of heart failure through personalized speech dynamics, showcasing si...
This paper explores the advantages of smooth activation functions in constant-depth neural networks, demonstrating their ability to achie...
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