ATHENA introduces an agentic team framework that autonomously manages the end-to-end computational research lifecycle via a knowledge-driven HENA loop to achieve validation errors of 10^{-14} in scientific computing and machine learning tasks.
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2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2025 2verdicts
UNVERDICTED 2representative citing papers
PURE is a three-component LLM system that extracts and maintains user profiles from reviews to outperform prior LLM recommenders on sequential Amazon tasks.
citing papers explorer
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ATHENA: Agentic Team for Hierarchical Evolutionary Numerical Algorithms
ATHENA introduces an agentic team framework that autonomously manages the end-to-end computational research lifecycle via a knowledge-driven HENA loop to achieve validation errors of 10^{-14} in scientific computing and machine learning tasks.
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LLM-based User Profile Management for Recommender System
PURE is a three-component LLM system that extracts and maintains user profiles from reviews to outperform prior LLM recommenders on sequential Amazon tasks.