Machine Learning
Popular
9 pages + references
Single column
ICLR LaTeX Template
International Conference on Learning Representations
Top venue for deep learning and representation learning. Open review process with author discussions.
About the ICLR Template
ICLR (International Conference on Learning Representations) is one of the fastest-growing and most influential machine learning conferences. Founded by Yoshua Bengio and Yann LeCun, ICLR pioneered the open peer review model through OpenReview, where reviews and author responses are publicly visible.
ICLR 2026 was held at the Riocentro Convention Center in Rio de Janeiro, Brazil (April 23–27, 2026). Submission deadlines for ICLR 2027 have not yet been announced — check iclr.cc for updates.
The ICLR LaTeX template uses a single-column format with a 9-page limit for the main text. Authors must use the official iclr style file, which can be obtained from the official Master-Template GitHub repository. The template file serves as a shell for writing your paper.
ICLR uses double-blind review. Authors are required to use the official style files, and tweaking them may be grounds for rejection. The conference covers topics in deep learning, representation learning, optimization, generative models, and applications of neural networks. The open review process allows reviewers and authors to engage in discussion during the review period.
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Formatting Requirements
| Property | Specification |
|---|---|
| Layout | Single column |
| Font Size | 10pt |
| Paper Size | US Letter |
| Document Class | iclr2026_conference |
| Citation Style | Author-year, natbib |
| Page Limit | 9 pages + references |
Key Dates
Submission
September 24, 2025 (for ICLR 2026)
Notification
January 25, 2026
Conference
April 23–27, 2026 — Rio de Janeiro, Brazil
Deep Learning
Representations
9 pages
9 pages + references
Frequently Asked Questions
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