recsys-review-process

name	recsys-review-process
description	Use when explaining or planning around ACM RecSys peer review — the mutually-anonymous model with at least three PC members and a Senior PC overseer, the rebuttal phase, how the reproducibility-crisis culture shapes reviewer priorities, the offline-versus-online evaluation lens, and how acceptance leads to ACM Digital Library publication.

RecSys Review Process

Use this to reason about review-stage strategy. Reopen the current Call for Contributions, the committees page, and any reviewer guidelines before making process claims — mechanics are cycle-specific.

Process model

• RecSys review is mutually anonymous (double-blind). Each submission is read by at least three PC members and overseen by a Senior PC member who synthesizes the recommendation.
• There is an author rebuttal phase (2026: June 4-9) for a short clarifying narrative.
• Reviewers weigh recommendation novelty, evaluation validity, reproducibility, clarity, and relevance to the recommender community — not raw metric wins alone.
• The most useful reply is a decision-focused clarification that gives the Senior PC a clean rationale for acceptance or rejection.
• Accepted papers are published in the ACM Digital Library, so camera-ready compliance and metadata matter as much as the initial decision.

Who reviews here, and what they distrust

• The pool is a single-domain recommender community: expect at least one reviewer who has internalized the field's reproducibility debate and will probe baseline tuning line by line.
• Because RecSys is topically tight, matches are close and an under-tuned comparison or a leaky split gets caught rather than skimmed past.
• Borderline offline-evaluation papers usually fall on one of three edges: baselines tuned less hard than the proposed method, a random split where a temporal one was needed, or an offline metric asserted to imply a deployment win with no bridge.

Scoring leverage table

Review dimension	What raises it	What sinks it
Recommendation novelty	A named user/item modeling or evaluation idea	An architecture swap with no recommendation-specific insight
Evaluation validity	Equal-budget baselines, temporal split, full-ranking metrics, variance	Untuned baselines, random split, sampled metrics reported as full
Deployment relevance	Off-policy estimate, simulator, or A/B result	"Offline nDCG rose, therefore users benefit"
Reproducibility	A runnable anonymous repository regenerating the tables	A promise to release code "upon acceptance" only
Clarity	One notation source, honest limitations	Buried assumptions; a random-split protocol left implicit

Stage-by-stage realism

• Initial reviews: triage by what the Senior PC would weigh, not by reviewer tone.
• Rebuttal: the window is short; an early, precise narrative on the central evaluation objection beats a late line-by-line reply (see recsys-author-response).
• Decision: the Senior PC synthesizes; one unresolved evaluation-validity objection outweighs several resolved clarity complaints.
• Post-decision: ACM Digital Library publication means the rights form and metadata become the final gate.

Vignette: reading a split decision

Two reviewers like the method; one flags that baselines were tuned only on defaults. At RecSys that single objection is decisive because it maps onto the community's reproducibility anxiety — so the rebuttal must resolve that thread, with the equal-budget grid, before polishing anything the other reviewers raised.

Output format

[Current stage] submitted / reviews / rebuttal / decision / camera-ready
[Decision actors] <PC reviewers / Senior PC>
[Likely leverage] <novelty / evaluation validity / deployment relevance / reproducibility / clarity>
[Forbidden moves] <identity leak / unseen new results / unsupported deployment claims>
[Next response move] <one action>