cikm-review-process
Use when reasoning about CIKM peer review — the EasyChair double-blind pipeline, the mixed IR/data-mining/knowledge-management reviewer pool, per-track evaluation criteria, the ACM Peer Review Policy including the no-AI-written-reviews rule, notification timing, and what actually moves borderline decisions.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cikm-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.
# CIKM Review Process CIKM review runs on EasyChair under double-blind rules, inside the ACM Peer Review Policy, and — its defining feature — in front of a reviewer pool drawn from three communities at once. Verified 2026 mechanics (source map, 2026-07-08): submissions closed in May/June, notification lands August 7, and referees are explicitly barred from using AI systems to write reviews. Whether 2026 includes an author response window is unconfirmed in either direction (待核实); plan without assuming one. ## The blended-pool effect A CIKM paper is typically read by people whose default standards differ: | Reviewer's home lane | What they instinctively grade | Complaint they file most | |---|---|---| | Information retrieval | Evaluation design, baselines, metric discipline | "Baselines are stale / significance untested" | | Data mining | Mechanism novelty, scalability, ablation logic | "Delta over the nearest KDD-line method unclear" | | KM / databases | Data model, integration cost, system realism | "Would not survive real schema/scale/noise" | The practical consequence: a paper optimized for one lane can draw its harshest review from another. Write the submission so each lane find
- The blended-pool effect
- Per-track criteria shift
- What moves a borderline
- Timeline realism for the live cycle
- Reading a CIKM review packet
- Confidentiality and integrity boundaries
- After the decision
- Scale realities
- Output format
What does the cikm-review-process skill do?
Use when reasoning about CIKM peer review — the EasyChair double-blind pipeline, the mixed IR/data-mining/knowledge-management reviewer pool, per-track evaluation criteria, the ACM Peer Review Policy including the no-AI-written-reviews rule, notification timing, and what actually moves borderline decisions.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill cikm-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.