| name | iclr-paper |
| description | Use this skill to help write, structure, polish, format, or review a paper for ICLR (International Conference on Learning Representations, any year), or whenever the user mentions 'ICLR', an OpenReview deep-learning submission, the iclr single-column style, the reproducibility statement, or the ICLR rebuttal/open-review process. Helps with ideation and narrative, section structure, sentence-level polishing, ICLR LaTeX formatting, figures and tables (including leaving sized placeholders for figures), citation verification, rebuttal preparation, and a submission checklist. Double-blind, public-review venue. Verify exact dates, page limits, and policies against that year's official ICLR Call for Papers. |
ICLR Paper Writing
Help the user take a deep-learning paper from idea to a polished, correctly formatted,
double-blind ICLR submission, and through the public rebuttal phase. You can brainstorm the
narrative, structure sections, polish prose, build LaTeX/figures/tables (or leave sized
placeholders), verify citations, and run a reviewer self-check.
How to use this skill
Load the matching reference file on demand (not all at once):
| User wants | Do this | Reference |
|---|
| Find the story / contribution / outline | nail the one-sentence contribution, then outline | references/ideation-and-structure.md |
| Draft or restructure a section | use the section blueprint | references/ideation-and-structure.md |
| Polish / tighten / "does this flow" | apply clarity principles + claim-evidence map | references/writing-and-polishing.md |
| Figures, tables, or placeholders | design or reserve space; generate plots | references/figures-and-tables.md, assets/ |
| Generate a flowchart / pipeline / experiment plot | run the helper scripts | references/generating-diagrams.md, assets/make_flowchart.py, assets/make_experiment_figures.py |
| Add citations | verify before citing; never hallucinate | references/citations.md |
| Set up LaTeX / fix formatting / convert venue | template workflow + pitfalls | references/latex-and-submission.md |
| Final pass before submitting | run the checklist below + 5-dimension self-review | this file + references/writing-and-polishing.md |
Be proactive: if the contribution and results are clear, deliver a full draft and flag
open choices, rather than asking permission section by section.
At a glance
- Conference: International Conference on Learning Representations (annual).
- Submission system: OpenReview — review is double-blind but reviews and rebuttals are
publicly visible, with an author-reviewer discussion period.
- Write to anticipate reviewer questions and leave room to answer them in rebuttal.
Dates change every year — check the current CFP
Do not rely on memorized dates. For the target cycle, open https://iclr.cc and read off the
abstract deadline, full-paper deadline, the rebuttal/discussion window, notification,
camera-ready, and conference dates/location. Rough rhythm (planning only): abstract and full
paper around late September of the prior year; conference the following spring.
Format (ICLR-specific)
- Template: official ICLR style for the target year (e.g.
iclrYYYY_conference.sty),
single column, 10pt.
- Length: about 9 pages of main text (recent cycles), with unlimited references and appendix;
camera-ready usually gets one extra page. Confirm the exact limit in the CFP.
- A reproducibility statement is expected; an (anonymized) code link helps scores.
- Recent cycles have required an LLM-usage disclosure; check the current CFP.
Structure notes specific to ICLR
Follow the general blueprint in references/ideation-and-structure.md, with ICLR emphasis:
- Reward strong empirical rigor: ablations that isolate the source of gains, multiple seeds,
error bars; representation/scaling analysis where relevant.
- Keep the 9-page main text focused; move proofs, full hyperparameters, and extra results to
the (unlimited) appendix.
- Include a clear reproducibility statement.
Rebuttal phase
- Plan time after notification for the discussion period.
- Prepare extra experiments reviewers are likely to ask for.
- Answer each reviewer point directly and concisely; update the PDF where allowed.
Submission checklist (ICLR)
When helping the user
- Ask whether the contribution is methodological, empirical, or theoretical, and what baselines exist.
- Offer to scaffold the ICLR LaTeX skeleton, draft contributions, organize appendix vs main
text, build figures as placeholders, or draft rebuttal responses.
