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Automatic Code Generation From Scientific Papers in Machine Learning by monye obed is a document available to read on EtoBox.

The document introduces PaperCoder, a multi-agent framework that automates the generation of code repositories from machine learning research papers, addressing the challenge of reproducibility in scientific research. PaperCoder operates in three stages: planning, analysis, and generation, utilizing specialized agents to produce high-quality, modular code without requiring prior implementations. Evaluations demonstrate that PaperCoder significantly outperforms existing baselines, with a high percentage of g

Author
monye obed
Language
EN