Autonomous agents, tool use, and agentic systems
Anthropic launches Claude Managed Agents in public beta — composable APIs for shipping production AI agents 10x faster Handles sandboxing...
Every agent I build forgets everything between sessions. I got tired of it and built brainctl. pip install brainctl, then: from agentmemo...
Hey everyone, I’m building a project for my university Machine Learning course called "Social network analysis using iterated game theory...
![[2601.00097] The Agentic Leash: Extracting Causal Feedback Fuzzy Cognitive Maps with LLMs](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
This paper presents a novel system using large language models (LLMs) to extract causal feedback fuzzy cognitive maps (FCMs) from text, d...
ARCTraj introduces a dataset and framework for modeling human reasoning in abstract problem-solving, providing insights into the iterativ...
This article explores the importance of ordering in the chain of thought for Transformers in arithmetic tasks, proposing a method to iden...
The paper introduces AgenticSciML, a multi-agent system designed to enhance scientific machine learning through collaborative reasoning, ...
The article presents Dataforge, an LLM-powered platform designed to automate data engineering processes, enhancing efficiency in preparin...
The paper presents HCLA, a human-centered multi-agent system designed for detecting anomalies in digital asset transactions, enhancing in...
AlphaOPT introduces a self-improving experience library for optimization modeling, enabling LLMs to learn from limited supervision and im...
The paper presents HYPER, a foundation model designed for inductive link prediction using knowledge hypergraphs, capable of generalizing ...
The paper presents an Agentic Framework with Large Language Models (LLMs) designed to automate complex vehicle routing problems (VRPs), e...
ParaCook introduces a benchmark for time-efficient planning in multi-agent systems, focusing on collaborative tasks inspired by cooking g...
This paper presents techniques to enhance data efficiency in reinforcement learning fine-tuning of large language models (LLMs) through d...
This article explores how decoder-only language models engage in internal planning, focusing on their ability to organize computations fo...
This article examines how AI maintains higher strategic tension in chess compared to human players, revealing insights into decision-maki...
This article explores the use of Large Language Models (LLMs) as tools for improving ontology alignment, demonstrating their effectivenes...
The paper introduces RV-Syn, a novel approach for synthesizing high-quality mathematical reasoning data using structured function librari...
The Sparse Latent Factor Forecaster (SLFF) proposes a new approach for predicting commodity futures by addressing forecast errors and enh...
The paper presents a framework for learning and encoding structurally enriched trajectories in complex environments, enhancing AI agents'...
This paper explores the application of weak neural networks in mastering impartial games like NIM, utilizing an AlphaZero-inspired multi-...
This article presents a novel approach using contextual quantum neural networks for predicting stock prices, enhancing accuracy and effic...
The paper introduces Fenchel-Young variational learning, a new class of variational methods that generalizes classical approaches, enhanc...
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