Paper2Code
About
Paper2Code is a tool powered by PaperCoder, a multi-agent Large Language Model (LLM) system, designed to automate the generation of executable code repositories directly from machine learning scientific papers. It employs a three-stage pipeline—planning, analysis, and code generation—each managed by specialized agents. This method has shown superior performance on Paper2Code and PaperBench benchmarks, producing faithful and high-quality implementations, supporting both OpenAI API and open-source models via vLLM.
Features
- Multi-agent LLM system (PaperCoder)
- Three-stage code generation pipeline (planning, analysis, code generation)
- Automated ML paper-to-code repository conversion
- Supports OpenAI API and open-source models (vLLM)
- Dedicated benchmark datasets and model evaluation framework
Supported Platforms
Links
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