This repository provides a comprehensive, opinionated checklist designed to help researchers in Computer Science ensure their papers meet quality standards for conference and journal submissions, aiming to prevent desk rejections. It covers critical aspects of paper writing, structure, and presentation, offering actionable advice for authors.

How It Works

The checklist is organized into thematic sections, from Title and Abstract to References and final Submission checks. Each item presents a specific guideline or question, often with explanations and justifications for why it's important. The approach is practical, focusing on common pitfalls and offering concrete advice, such as limiting sentence length or ensuring figures are grayscale-compatible.

Quick Start & Requirements

This is a checklist, not a software tool. It is intended to be used manually by authors during the writing and revision process. No installation or specific software requirements are needed beyond a PDF viewer or text editor.

Highlighted Details

• Detailed guidance on abstract structure, including the inclusion of quantitative results.
• Emphasis on clear contribution statements and the use of compelling figures in the introduction.
• Specific advice on managing related work, including LLM usage caveats and baseline selection.
• Thorough checks for experimental rigor, reproducibility, and insightful analysis.
• Strict guidelines on writing style, figure/table presentation, and reference formatting.

Maintenance & Community

The project is described as a "living document" and welcomes contributions via Pull Requests. Specific contributors, sponsorships, or community channels (like Discord/Slack) are not mentioned in the README.

Licensing & Compatibility

The repository is part of the cs-paper-checklist project. The specific license is not stated in the README, but contributions are welcomed via PR, suggesting an open-source model.

Limitations & Caveats

The checklist is opinionated, and some items are subjective. It explicitly warns against trusting LLMs for literature review without manual verification. The effectiveness relies entirely on the author's diligence in applying the checklist.