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paper-replication

Convert research paper PDFs or text into runnable PyTorch implementations.

16|1|Updated Jan 2, 2026
Search Tags:#PyTorch#PDF#code-generation#deep-learning#paper-replication#architecture-extraction#research-reproducibility
One-click install
npx skills add https://github.com/bahayonghang/my-claude-code-settings --skill paper-replication
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: paper-replication
Source: https://github.com/bahayonghang/my-claude-code-settings/tree/main/skills/paper-replication
Command: npx skills add https://github.com/bahayonghang/my-claude-code-settings --skill paper-replication

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The skill helps researchers and engineers reproduce deep learning papers by converting PDF or text descriptions into runnable PyTorch code and project scaffolds.

Core Features & Use Cases

  • Paper-to-code translation: Extract architecture details, equations, and training setups from papers (PDF or text) and generate working PyTorch modules.
  • Automated scaffolding: Produce a complete project skeleton including model classes, dataset loaders, and training templates.
  • Use Case: If you have a new paper on a CNN architecture, feed its PDF and obtain a ready-to-run PyTorch implementation with an example training script.

Quick Start

Use the skill to convert a provided paper PDF into a PyTorch-compatible implementation with a runnable training loop.

Frequently Asked Questions about paper-replication

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I convert a research paper PDF into runnable PyTorch code?▼

To convert a research paper PDF into runnable PyTorch code, you feed the document to the skill, which extracts architecture details, equations, and training setups to generate working PyTorch modules and project scaffolds.

What is the best way to reproduce deep learning models from research papers?▼

The best way to reproduce deep learning models is by automatically translating text or PDF descriptions into ready-to-run PyTorch implementations, extracting architecture details, training setups, and evaluation protocols.

Does this paper replication tool generate complete training templates and dataset loaders?▼

Yes, this paper replication tool generates complete project scaffolds including runnable PyTorch module code, dataset loaders, and training templates alongside the extracted model architecture.

Can I extract a CNN architecture from a text description and generate a PyTorch implementation?▼

Yes, you can extract a CNN architecture from a text description and generate a PyTorch implementation with an example training script, ensuring all model classes and evaluation protocols are scaffolded.

What components do I need to set up before reproducing PyTorch model architectures?▼

You need to provide the source research paper as a PDF or text description, ensuring the deep learning paper contains extractable architecture details and training setups for successful PyTorch code generation.

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