Autonomous agents, tool use, and agentic systems
Unlike static, rules-based systems, AI agents can learn, adapt, and optimize processes dynamically. As they interact with data, systems, ...
I’ve been working on building an agentic AI workflow system for business use cases and one thing became very clear very quickly. This is ...
Something I've been thinking about after spending a few months actually trying to build my own AI agent: the biggest trap in this space i...
![[2602.16833] VAM: Verbalized Action Masking for Controllable Exploration in RL Post-Training -- A Chess Case Study](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
The paper presents Verbalized Action Masking (VAM), a novel method for enhancing exploration in reinforcement learning (RL) post-training...
The paper presents HiVAE, a hierarchical variational architecture designed to enhance AI's theory of mind capabilities, enabling better i...
This study investigates the effectiveness of AI-mediated feedback on student revisions in a large undergraduate course, revealing that AI...
The PREFER ontology aims to standardize data in precision fermentation, enhancing interoperability and data accessibility across bioproce...
This article presents a geometric analysis of optimization dynamics in transformers, focusing on the phenomenon of grokking, where models...
The paper presents PETS, a framework for optimal trajectory allocation aimed at enhancing test-time self-consistency in machine learning ...
DeepVision-103K introduces a comprehensive dataset designed to enhance reinforcement learning with verifiable rewards, significantly impr...
The paper presents a deterministic semantic state substrate for AI, demonstrating a novel compute envelope that maintains performance acr...
The paper presents APEX-SQL, a novel framework for Text-to-SQL that enhances interaction with complex databases through agentic explorati...
The paper presents the HIPE-2026 evaluation lab focused on extracting person-place relations from multilingual historical texts, enhancin...
AutoNumerics is a multi-agent framework that autonomously designs and verifies numerical solvers for PDEs from natural language, outperfo...
The paper introduces the AI Gamestore, a platform for evaluating machine general intelligence through human games, highlighting its poten...
The paper presents KLong, an open-source LLM agent designed for solving extremely long-horizon tasks by utilizing trajectory-splitting SF...
This paper evaluates Chain-of-Thought (CoT) reasoning in AI through new metrics of reusability and verifiability, revealing limitations o...
The paper presents a novel framework integrating formal verification with deep learning for improved image retrieval, addressing the limi...
MedClarify is an AI agent designed to enhance medical diagnosis by generating case-specific follow-up questions, improving diagnostic acc...
The paper introduces 'Web Verbs', a set of typed abstractions designed to improve task composition on the Agentic Web, enhancing reliabil...
The paper presents the Large Behavioral Model (LBM), a novel AI framework designed to enhance the prediction of human decision-making in ...
This article explores a methodological experiment using AI agents to enhance research in Taiwan's humanities and social sciences, proposi...
This paper presents a framework for online construction of symbolic causal world models, enhancing agents' decision-making through contin...
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