Analysis updated 2026-07-03
Start a CVPR or NeurIPS submission using a pre-formatted Overleaf template instead of building from scratch.
Write a rebuttal response to reviewer comments using a template that matches the expected conference format.
Design a conference poster by adapting a finished example from a published CVPR or ECCV paper.
Structure a PhD dissertation at HKU or an undergraduate thesis at Sun Yat-sen University using the provided templates.
| guanyingc/latex_paper_writing_tips | sjtug/sjtuthesis | ctex-org/lshort-zh-cn | |
|---|---|---|---|
| Stars | 3,749 | 3,772 | 3,671 |
| Language | TeX | TeX | TeX |
| Setup difficulty | easy | moderate | moderate |
| Complexity | 1/5 | 2/5 | 2/5 |
| Audience | researcher | researcher | researcher |
Figures from each repo's GitHub metadata at analysis time.
Templates open directly in Overleaf, no local LaTeX install required.
LaTeX is a document preparation system used widely in academic research. This repository is a practical guide for graduate students and researchers who are new to writing papers with LaTeX. The main resource is a PDF article with tips for paper writing, accompanied by working examples of tables and figures that the author used in published research. Because these examples come from actual conference papers, readers can see exactly how polished results look and copy the structure for their own work. The repository collects LaTeX templates specifically formatted for major computer vision and machine learning conference submissions: CVPR, ICCV, NeurIPS, and ECCV. These templates are available on Overleaf, a browser-based LaTeX editor, so you do not need to install anything locally. There are separate templates for the main paper, for rebuttal responses (the short reply authors send when reviewers raise concerns), and for supplementary material. The project also includes poster templates for academic conferences, again drawn from the author's actual published work at CVPR, ECCV, ICCV, and NeurIPS. Seeing a finished conference poster alongside its LaTeX source helps new researchers understand how the layout pieces fit together and how to adapt them. Two thesis templates are also shared: one for a PhD dissertation at the University of Hong Kong and one for undergraduate thesis formatting at Sun Yat-sen University. These are more specialized but useful if you are at either institution and need a starting point that matches the expected format. A small Python utility for creating and cropping figures rounds out the collection, along with pointers to related resources from other contributors. The project's main audience is new graduate students in computer vision or machine learning who need to write their first conference paper and are not yet comfortable with LaTeX. The examples are concrete and drawn from real publications, which makes the learning curve lower than reading generic documentation.
A practical LaTeX guide for new grad students in AI/ML research, real conference paper and poster templates for CVPR, NeurIPS, ICCV, and ECCV, with writing tips from published work.
Mainly TeX. The stack also includes TeX, LaTeX, Python.
Open source, free to use and adapt the templates for your own academic papers.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
Verify against the repo before relying on details.