Autonomous agents, tool use, and agentic systems
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? ...
![[2601.00809] A Modular Reference Architecture for MCP-Servers Enabling Agentic BIM Interaction](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
Abstract page for arXiv paper 2601.00809: A Modular Reference Architecture for MCP-Servers Enabling Agentic BIM Interaction
Abstract page for arXiv paper 2511.11483: ImAgent: A Unified Multimodal Agent Framework for Test-Time Scalable Image Generation
The CXReasonAgent integrates large language models with diagnostic tools for improved reasoning in chest X-ray interpretations, addressin...
This paper evaluates the stochasticity in Deep Research Agents (DRAs), highlighting how variability in their outputs can impact research ...
AgentDropoutV2 introduces a novel pruning framework to enhance information flow in Multi-Agent Systems by dynamically correcting errors d...
The paper presents MSINO, a novel curvature-aware optimization framework for training neural networks on Riemannian manifolds, enhancing ...
This paper presents a novel approach to mitigate the 'legibility tax' in large language models by decoupling the prover-verifier game, al...
This paper presents a groundbreaking model-free agent, AIQI, which achieves asymptotic optimality in reinforcement learning, expanding th...
This paper explores the limitations of optimization-based AI systems, arguing that they cannot be norm-responsive due to inherent archite...
The paper presents ReCoN-Ipsundrum, an inspectable AI agent that integrates affect-coupled control with a recurrent persistence loop, exp...
SC-Arena introduces a natural language benchmark for evaluating single-cell reasoning in large language models, addressing gaps in curren...
The paper presents ESAA, an architecture for autonomous agents using event sourcing to enhance state management and execution in LLM-base...
This article explores decentralized ranking aggregation using gossip algorithms for Borda and Copeland consensus, addressing challenges i...
This paper presents a decision-theoretic framework for understanding steganography in large language models (LLMs), addressing the challe...
This paper proposes the 'Trinity of Consistency' as a foundational principle for developing General World Models in AI, emphasizing modal...
The paper presents PATRA, a novel model for Time Series Question Answering that enhances reasoning by incorporating pattern awareness and...
This paper presents Hierarchy-of-Groups Policy Optimization (HGPO), a novel approach to improve group-based reinforcement learning for lo...
This paper explores sample-efficient generalized planning through learned transition models, demonstrating improved performance over trad...
The paper presents a multi-agent system, MALLET, designed to reduce emotional stimulation from sensational content, enhancing consumer de...
This article presents a theoretical analysis of multi-agent imitation learning (MAIL) in linear Markov games, introducing a novel interac...
This article explores how autonomous AI agents can form tribal behaviors similar to those depicted in 'Lord of the Flies', leading to ine...
This paper introduces AILS-AHD, a novel approach that utilizes Large Language Models to enhance the Capacitated Vehicle Routing Problem (...
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