Paper Code Finder

Paper-Code-Finder: Code Discovery for Academic Papers

This skill locates the official or unofficial source code implementations for academic papers, utilizing highly efficient search strategies specifically optimized for the AI/ML ecosystem.

1. Input Processing & Entity Extraction

First, analyze the user's input to extract key metadata:

• Title, Authors, Affiliations: Extract these from the prompt, PDF, arXiv link, or DOI.
• ML Framework Semantic Extraction: If a PDF or abstract is provided, scan the "Experiments" or "Implementation Details" section for keywords like PyTorch, JAX, Flax, TensorFlow, or Diffusers. Use this to narrow down your search queries.

2. Search Strategy (The Waterfall)

Execute a structured, sequential search to find the code. Progress through these steps sequentially until you find a match. For highest precision, explicitly use the exa-search or tavily-web skills/tools if they are available to you.

Phase 1: The Fast-Path (PapersWithCode)

1. Search "[Title] paperswithcode". This is the most reliable database.

Phase 2: The Hugging Face & Mega-Repo Hunter

1. Search "[Title] site:huggingface.co/papers" and "[Title] site:huggingface.co".
2. If the paper is about foundational models, search for pull requests in mega-repos: "[Title] huggingface/transformers github" or "[Title] huggingface/diffusers github".

Phase 3: The Deep-Path (Author Profile Hunting)

If the above fail, the repo likely has an obscure name.

1. Direct GitHub: Search "[Title] [Framework] site:github.com".
2. Find the Authors: Identify the First Author and the Last Author (Principal Investigator).
3. Find their GitHub: Search "[Author Name] [University/Affiliation] site:github.com".
4. Inspect the Profile: Look at their pinned repositories or search within their GitHub profile for repos created around the paper's publication year.
5. Personal Websites: Search for the author's academic homepage (e.g., "[Author Name] [University] homepage").

3. Verification & Classification

When repositories are found, evaluate them:

• Official Implementation: Owned by the paper's authors, or explicitly linked inside the paper text/author's website/PapersWithCode.
• Unofficial Implementation: A community reproduction. Check the stars and recent activity to gauge quality.

4. Expected Output Format

Return a concise, direct answer to the user. Do not write a long essay. Always include the framework if you discovered it.

If Official Code is Found:

✅ Official Implementation Found: Repository Name (Implemented in [Framework])

If Only Unofficial Code is Found:

⚠️ No Official Code Found, but community implementations exist:

• Repo Name (⭐ XXX) - Unofficial [Framework] implementation.

If No Code Exists:

❌ No Code Found. I searched PapersWithCode, Hugging Face, direct GitHub, and the authors' profiles ([Author 1], [Author 2]), but could not find any public implementations.