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ModeledConference on Learning Theory

The COLT 2026 review form, explained

Simulate COLT 2026-style learning-theory reviews: summary of results, significance and novelty relative to known bounds, correctness of the proofs, clarity, comments, an overall score and confidence.

Modeled, not official. COLT reviews in a private CMT form and publishes no reviewer guidelines. Every field and scale here is modeled on standard learning-theory reviewing (contribution, correctness, significance, clarity) and the CFP's reviewing philosophy.

COLT 2027 paper deadline (estimated)~Feb 4, 2027 · 23:59 AoE~4 months
Overall score
Overall Score, 1–5
Sub-scores
None
Confidence
1–5
Form fields
7
Author checklist
3 items

How COLT reviewers read your paper

COLT asks reviewers to judge whether the work is close to being ready for publication and to help guide it there with constructive feedback. Papers are evaluated primarily on the main text, though all proofs must be included; there is an author response and discussion phase. Theory papers are judged on the significance and novelty of their results and techniques and on technical correctness, not on empirical evaluation.

  • Constructive: aim to help the paper reach publication quality.
  • Compare results precisely to the best known bounds and cite the prior work.
  • Say exactly which proofs were checked; point to specific steps for any error.
  • Do not ask for experiments unless the paper's claims are empirical.

Where the bar sits. COLT 2026 accepted about 190 papers; submission counts are not published (historically ~30% acceptance). On this modeled 1–5 scale a mean of ≥ 3.5 is a rough proxy for acceptance.

The reviewer form, field by field

In the order reviewers see it, with every score and its official wording.

  1. 01

    Summary Of Results

    Free text

    State the main theorems informally: setting, assumptions, the bounds or characterizations proved, and how they compare to the best known results.

  2. 02

    Significance And Novelty

    List of points

    What is new relative to prior bounds and techniques (cite them), whether the techniques are of independent interest, and how the results advance learning theory.

  3. 03

    Technical Correctness

    List of points

    Which proofs were checked and how carefully; any gaps, errors or unjustified steps (with locations); whether assumptions are reasonable and stated. Judgment rests primarily on the main text, but proofs must be complete in the appendix.

  4. 04

    Clarity And Presentation

    Free text

    Are the setting, results and proof ideas explained clearly in the main text?

  5. 05

    Comments And Questions For The Authors

    List of points

    Constructive suggestions and questions for the author response, aimed at bringing the paper closer to publication.

  6. 06

    Overall Score

    Score · 1–5

    Overall recommendation.

    1. 5Strong accept
    2. 4Accept
    3. 3Borderline
    4. 2Reject
    5. 1Strong reject
  7. 07

    Confidence

    Score · 1–5

    How certain you are, including how carefully the proofs were checked.

    ScoreMeaning
    5Expert checked the proofs carefully and know the related literature well
    4Confident checked the key proofs
    3Fairly confident read the proofs at a high level
    2Somewhat confident did not check the proofs
    1Educated guess

Area chair meta-review

COLT area chairs lead discussion and recommend; the form is not public.

  • Accept
  • Reject

COLT submission requirements

Reviewers check these. Gaps are easy points to lose.

  1. At most 12 PMLR-format pages, plus unlimited references and appendices
  2. All proofs included (main text should convey the key ideas)
  3. Anonymized (double-blind)

Policy on LLMs in reviewing

COLT 2026 reviewers must not share submissions with any LLM; models may be used like books or Wikipedia to understand technical points, without leaking confidential information.

Read the official policy

Author mode is for your own unpublished work. If you are an assigned reviewer, follow these rules: you are responsible for your review.

See your paper through COLT reviewers' eyes

Three simulated reviewers fill in exactly this form for your draft, then an area chair writes the meta-review. Every point links to the passage it's about. Your first three runs are free.

Review my paper — 3 free

reviewpaper.ai is not affiliated with COLT or its organizers. Forms change between cycles; always check the official source.