Autonomous agents, tool use, and agentic systems
Hi everyone, I’ve been exploring MCP and integrating tools like n8n with Claude Code, and I’m trying to understand how practical this rea...
Browser Rendering now exposes the Chrome DevTools Protocol, which means MCP clients can access a remote browser directly. That’s a pretty...
Anthropic launches Claude Managed Agents in public beta — composable APIs for shipping production AI agents 10x faster Handles sandboxing...
![[2602.14795] Return of the Schema: Building Complete Datasets for Machine Learning and Reasoning on Knowledge Graphs](https://arxiv.org/static/browse/0.3.4/images/arxiv-logo-fb.png){kind=logo}
This paper presents a novel resource for building complete datasets that integrate schema and ground facts for machine learning and reaso...
The paper explores how advanced AI models exhibit complex reasoning in simulated nuclear crises, revealing insights into strategic decisi...
This paper introduces a novel position encoding strategy, Random Float Sampling (RFS), which enhances the length generalization capabilit...
WebWorld introduces a large-scale simulator for training web agents, utilizing over 1 million open-web interactions to enhance generaliza...
The paper proposes Evolutionary System Prompt Learning (E-SPL) to enhance reinforcement learning in large language models (LLMs) by evolv...
The paper presents S2SServiceBench, a multimodal benchmark designed to enhance the effectiveness of last-mile subseasonal-to-seasonal (S2...
This paper presents a method to eliminate planner bias in goal recognition using multi-plan dataset generation, enhancing the evaluation ...
This paper introduces Base Score Extraction Functions in gradual argumentation, enhancing decision-making and AI transparency by mapping ...
The paper presents Arbor, a framework designed to enhance the navigation of critical conversation flows in high-stakes environments like ...
This article presents a novel approach to chemical language models specifically for natural products, showcasing the effectiveness of sta...
The paper introduces Quantized Reinforcement Learning (QuRL), a method aimed at improving the efficiency of reinforcement learning in lar...
The paper introduces Experiential Reinforcement Learning (ERL), a new paradigm that enhances learning efficiency in language models by in...
MATEO introduces a benchmark for assessing temporal reasoning in Large Vision Language Models (LVLMs), focusing on multimodal inputs and ...
The paper presents iML, a multi-agent framework for automated machine learning that enhances transparency and modularity, addressing limi...
This technical report presents a comprehensive risk analysis framework for frontier AI, focusing on emerging threats and mitigation strat...
This study explores the efficacy of reasoning traces in neural networks, introducing a large dataset to assess how well models generalize...
Pawsterior introduces a variational flow-matching framework to enhance simulation-based inference (SBI), addressing constraints in struct...
The paper presents AutoWebWorld, a framework that synthesizes verifiable web environments using Finite State Machines, enhancing the trai...
The paper introduces the Mean Velocity Policy (MVP) for reinforcement learning, which enhances one-step action generation by modeling the...
The paper introduces GRAIL, a method for recognizing agent goals through imitation learning, enhancing goal recognition accuracy in AI sy...
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