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paper-review

Review machine learning papers against NeurIPS, ICML, and ICLR standards.

1|2|Updated Jan 15, 2026
Search Tags:#academic publishing#scientific writing#peer review#research evaluation#neurips#icml#ml paper review
One-click install
npx skills add https://github.com/ihmorol/unsw-nb15-handling-binary-multiclass-ids --skill paper-review-ihmorol
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: paper-review
Source: https://github.com/ihmorol/unsw-nb15-handling-binary-multiclass-ids/tree/main/.opencode/skills/paper-review
Command: npx skills add https://github.com/ihmorol/unsw-nb15-handling-binary-multiclass-ids --skill paper-review-ihmorol

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a structured and rigorous framework for reviewing machine learning papers, ensuring comprehensive evaluation against top-tier academic standards.

Core Features & Use Cases

  • Structured Review: Follows a systematic process covering claims, novelty, technical correctness, experimental rigor, reproducibility, and ethics.
  • Actionable Feedback: Generates detailed strengths, major/minor concerns with concrete fixes, and suggested experiments.
  • Use Case: A researcher needs to submit a paper to NeurIPS and wants a pre-submission review that mimics the conference's expectations, identifying potential weaknesses and areas for improvement before formal submission.

Quick Start

Use the paper-review skill to review the attached document 'ml_paper_final.pdf'.

Frequently Asked Questions about paper-review

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

FAQPage Schema
What is a structured peer review for machine learning papers?▼

A structured peer review for machine learning papers systematically evaluates claims, novelty, technical correctness, experimental rigor, reproducibility, and ethical considerations to generate detailed feedback and ratings based on top-tier academic standards.

How do I review an ML paper before submitting to NeurIPS or ICML?▼

To review an ML paper before submitting to NeurIPS or ICML, use the paper-review skill on your attached PDF document to perform a comprehensive evaluation that mimics conference expectations and identifies potential weaknesses.

Can I get suggested experiments and actionable fixes for my research paper?▼

Yes, you can get suggested experiments and actionable fixes for your research paper. The review process generates detailed feedback including major and minor concerns with concrete fixes, alongside recommended additional experiments.

Does the ML paper review process evaluate technical correctness and reproducibility?▼

Yes, the ML paper review process evaluates technical correctness and reproducibility. It follows a systematic framework covering claims, novelty, experimental rigor, and ethical considerations to ensure comprehensive research evaluation.

What is the best way to identify weaknesses in an academic publishing manuscript?▼

The best way to identify weaknesses in an academic publishing manuscript is to perform a rigorous pre-submission review against top-tier conference standards, which highlights specific strengths, concerns, and areas for improvement.

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