Autonomous agents, tool use, and agentic systems
150 clones yesterday. 43 stars in 3 days. Every agent framework you've used (LangChain, LangGraph, Claude Code) assumes agents are tools ...
Gloat Agentic AI opens the door to new HCM-based AI agents for HR, in an open toolset that works in any agent platform.
![[2603.10062] Multi-Agent Memory from a Computer Architecture Perspective: Visions and Challenges Ahead](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Abstract page for arXiv paper 2603.10062: Multi-Agent Memory from a Computer Architecture Perspective: Visions and Challenges Ahead
The paper presents VCC-Net, a visual cognition-guided cooperative network aimed at enhancing chest X-ray diagnosis through improved human...
The paper introduces CCCaption, a dual-reward reinforcement learning framework designed to enhance image captioning by optimizing for com...
The article presents PPCR-IM, a system for multi-layer DAG-based reasoning in public policy, enhancing the mapping of social indicators a...
The paper presents Self-Correcting VLA, a novel approach in robotics that enhances vision-language-action models by integrating sparse wo...
The paper presents Structurally Aligned Subtask-Level Memory, a novel approach for enhancing software engineering agents by improving mem...
This article explores the challenges of retrieving public service information in low-resource environments, focusing on food pantry acces...
This article presents a novel Virtual Biopsy framework for diagnosing intracranial tumors using MRI, addressing the challenges of traditi...
This paper presents MIGRASCOPE, a new framework for evaluating RAG retrievers, emphasizing the need for systematic benchmarks and metrics...
This paper explores the evolving relationship between humans and AI, proposing a framework for harmonious coexistence termed 'symmetrical...
This article presents a novel Gaussian Particle Representation for interpreting PDE operators, enhancing interpretability and efficiency ...
The paper introduces LiLo-VLA, a modular framework for long-horizon manipulation in robotics, enhancing performance through object-centri...
The paper presents GradAlign, a novel method for selecting training data in reinforcement learning for large language models, enhancing p...
This paper explores training strategies for collaborative agents, emphasizing strategic risk aversion to enhance generalizability and rob...
The paper 'Revisiting Text Ranking in Deep Research' explores the effectiveness of text ranking methods in deep research settings, focusi...
The paper presents a novel framework, MMA-RAG^T, for enhancing the security of multimodal agentic retrieval-augmented generation systems ...
The paper introduces MINAR, a toolbox for mechanistic interpretability in neural algorithmic reasoning, enhancing understanding of GNNs' ...
ECHOSAT introduces a global tree height map that captures temporal forest dynamics, enhancing carbon monitoring and disturbance assessmen...
The paper explores how reinforcement learning agents' actions depend on internal information, revealing structural conditions affecting b...
This paper introduces the Asymmetric Confidence-aware Error Penalty (ACE) to enhance reinforcement learning by addressing overconfident e...
The paper discusses how AI is transforming enterprise structures by reducing coordination costs, leading to the emergence of the 'Headles...
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