Autonomous agents, tool use, and agentic systems
I've been experimenting with multi-agent AI systems and ended up building something more ambitious than I originally planned: a fully ope...
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
This survey paper explores the development of personalized LLM-powered agents, focusing on their foundations, evaluation metrics, and fut...
The paper presents a two-stage framework for enhancing large reasoning models (LRMs) by addressing overthinking in low-complexity queries...
The paper presents AHBid, a novel hierarchical bidding framework for cross-channel advertising that enhances budget allocation and adapta...
The paper presents AVDE, a novel framework for decoding visual information from EEG signals, addressing challenges in modality bridging a...
MobilityBench introduces a benchmark for evaluating LLM-based route-planning agents, addressing challenges in real-world mobility scenari...
The paper presents SideQuest, a novel model-driven approach for managing KV cache in long-horizon reasoning tasks, achieving significant ...
This paper explores the concept of strategy executability in mathematical reasoning, highlighting the differences between human and model...
CourtGuard introduces a model-agnostic framework for zero-shot policy adaptation in LLM safety, enhancing adaptability and performance wi...
This article presents a framework called AHCE for enhancing Large Language Model (LLM) agents through effective human collaboration, sign...
This paper presents an agentic AI framework for optimizing intent-driven operations in cell-free O-RAN, enhancing collaboration among age...
The paper discusses how cognitive models and AI algorithms can serve as templates for designing modular language agents, addressing limit...
This paper presents a mathematical framework for understanding agency and intelligence in AI systems, introducing the concept of bipredic...
The paper presents Metacognitive Behavioral Tuning (MBT), a framework designed to enhance large reasoning models by incorporating human-l...
The paper introduces VeRO, an evaluation harness designed for optimizing coding agents through structured evaluation and benchmarking, ad...
The paper introduces ConstraintBench, a benchmark designed to evaluate large language models (LLMs) on direct constrained optimization ta...
The paper presents Contrastive World Models (CWM) for enhancing action feasibility learning in embodied agents, improving action scoring ...
This article presents a framework for evaluating AI agent decisions in AutoML pipelines, emphasizing decision-centric metrics over tradit...
This paper analyzes latent reasoning methods under varying supervision levels, revealing key issues like shortcut behavior and the trade-...
ArchAgent is an AI-driven system that automates computer architecture discovery, achieving significant performance improvements in cache ...
This paper explores a probabilistic framework for collective decision-making among agents that can assess their own reliability and selec...
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