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Magentic-One: A Generalist Multi-Agent System
The paper titled “Magentic-One: A Generalist Multi-Agent System For Solving Complex Tasks” presents a significant advancement in the field of Artificial Intelligence (AI), particularly in the domain of multi-agent systems.
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Into The Unknown Unknowns
The research paper “Into The Unknown Unknowns: Engaged Human Learning Through Participation In Language Model Agent Conversations” introduces Co-STORM, an innovative system addressing the challenge of discovering unknown unknowns in information seeking.
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Agent-As-A-Judge: Evaluate Agents With Agents
The paper titled “Agent-As-A-Judge: Evaluate Agents With Agents” addresses a critical challenge in the field of Artificial Intelligence (AI) concerning the evaluation methodologies for agentic systems.
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Agent S: An Open Agentic Framework
The rapid advancement of technology has significantly transformed human-computer interaction (HCI), leading to the development of autonomous agents capable of performing complex tasks. These agents are designed to enhance user experience by automating repetitive and intricate processes, thereby improving efficiency and accessibility.
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TaskGen Framework: An Innovative Approach for AI Engineers
TaskGen is an open-sourced agentic framework designed to enhance task execution by decomposing complex challenges into manageable subtasks. This document provides a comprehensive overview of the TaskGen framework, emphasizing its modular architecture, innovative methodologies, and practical applications in AI engineering.
Tag: ARITIFICIAL_INTELLIGENCE_AGENTS
AI entities designed to perceive, decide, and act autonomously. Explore types, architectures, and applications of intelligent agents.