colt-review-process
Use when reasoning about COLT (Conference on Learning Theory) peer review — the double-anonymous-with-informed-area-chair model, correctness-first evaluation by expert theorists, the rebuttal stage before decisions, single-track acceptance stakes, and how PMLR publication and the community's proof culture shape outcomes.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill colt-review-process --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# COLT Review Process Use this to plan around COLT's review pipeline. Process facts below were verified against the COLT 2026 CFP on 2026-07-08; mechanics are re-decided by each edition's program chairs, so reconfirm in the cycle you are in. ## The 2026 pipeline - Submission via Microsoft CMT by February 4, 2026 (AoE) for the 39th edition. - Double-anonymous refereeing with a twist: reviewers do not see author names, but the area chair handling the paper does, and may reveal identities to a reviewer during the rebuttal period on request when needed for a proper review. - Initial reviews go to authors before decisions; a rebuttal window follows. - Accepted papers appear in PMLR (v291 carried COLT 2025; the 2026 volume number is assigned at publication). - COLT is run by the Association for Computational Learning, with program chairs rotating yearly; the 2026 chair names were not published in a form verifiable at the access date (待核实 — check learningtheory.org/colt2026/). ## Who reviews a COLT paper The pool is learning theorists: statistical learning, online learning and bandits, optimization theory, RL theory, privacy, and adjacent CS theory. Practical consequences: - Expect at lea
- The 2026 pipeline
- Who reviews a COLT paper
- What the scores actually track
- Decision dynamics
- Reading a COLT review
- After the decision: reading the outcome
- Confidentiality and conduct
- Cycle-volatility warnings
- Output format
What does the colt-review-process skill do?
Use when reasoning about COLT (Conference on Learning Theory) peer review — the double-anonymous-with-informed-area-chair model, correctness-first evaluation by expert theorists, the rebuttal stage before decisions, single-track acceptance stakes, and how PMLR publication and the community's proof culture shape outcomes.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill colt-review-process --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 909 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.