Skills Artificial Intelligence RecSys Submission Audit Checklist

RecSys Submission Audit Checklist

v20260724
recsys-submission
This comprehensive audit checklist is designed for authors submitting papers to the ACM RecSys conference. It guides users through selecting the correct specialized track (Main, Industry, Reproducibility), adhering to strict page budgets, ensuring thorough double-blind anonymization, and mitigating common submission risks like identity leaks and improper data splitting.
Get Skill
154 downloads
Overview

RecSys Submission

Run this audit before anything is uploaded to the RecSys submission system. RecSys is a single-community but multi-track venue: the same manuscript can be legal in one track and desk-rejectable in another, so the audit begins with "which track is this PDF for?" and only then checks format. Reopen the current edition's Call for Contributions — every number below is a 2026-cycle anchor (verified 2026-07-09), not a permanent rule.

Pick the track before the format

For 2026 RecSys reorganized its lineup: it dropped the Late-Breaking Results (LBR) poster track and added Research & Practice (R&P) Notes. Route the contribution first.

Track 2026 budget What belongs here
Main - long paper 8 content pages A rounded recommendation contribution with offline (and ideally online) evidence
Main - short paper 4 content pages One focused, complete finding
Main - Past, Present & Future 4 content pages Reflective/forward-looking position on a recommendation topic
Reproducibility see current CFP Repeating, refuting, or re-scoping prior results; datasets/frameworks for future reproduction
Industry see current CFP Deployed systems, production constraints, live A/B evidence
Resource / Dataset see current CFP A community dataset or software resource with build methodology
R&P Notes (posters) see current CFP Short findings/experiences; replaces LBR for 2026

References are excluded from the page count; appendices count inside it. Use the ACM two-column template unmodified — no margin, font, or spacing surgery.

Anonymization for recommender papers specifically

Generic double-blind advice misses the leaks recommender papers actually carry:

  • Proprietary logs and platform. "Interaction logs from our video platform in region X" can name the company. Keep the statistics, genericize the source.
  • Deployed system names. If the ranker already runs in production under a public name, the name de-anonymizes; rename for review or argue from the current policy on preprints.
  • The anonymous repository. RecSys expects a code/data link inside the paper rather than a supplement upload — mirror it to an anonymized host and strip the owner, commit authors, and cluster paths from history.
  • Self-citations in third person; acknowledgements and funding removed; PDF metadata stripped.

Blocking risks

  • Wrong track for the contribution (a deployed-system paper squeezed into a Main long paper, or a reproduction study submitted as a novel-method paper).
  • Over budget once appendices are counted inside the limit.
  • Identity leak via logs, platform, deployed system name, or repository owner.
  • Untuned baselines or a random split on sequential data — not a format desk reject, but the fastest route to a low score (see recsys-experiments).
  • Parallel submission of the same work to another venue.

Desk-reject and triage table

Trigger Severity at RecSys Repair window
Over budget (appendix counted in) Desk reject None after the deadline
Template tampering Desk reject or chair flag None
Identity leak in PDF, logs, or repository Desk reject None
Wrong track's submission form Desk reject or forced move Usually none
Parallel/dual submission Desk reject at any time None
Baselines untuned; random split on session data Review-stage damage Only before the deadline

Final-week sequence for an offline-evaluation paper

  1. Freeze the split: regenerate every ranking table from the versioned dataset and a temporal split so the PDF and the anonymous repository agree.
  2. Re-run baseline tuning last under an equal budget; a stale, under-tuned baseline is the classic reviewer catch when the numbers move.
  3. Compress into the content-page budget by demoting per-dataset analyses to the appendix or repository, never by shrinking floats.
  4. Anonymity sweep: PDF metadata, acknowledgements, log provenance, deployed-system name, repository owner.
  5. Confirm the submission-form abstract matches the PDF abstract and the track is correct.
# Pre-upload checks that catch the silent killers
pdfinfo paper.pdf | grep -iE "author|creator"                 # metadata identity leak
grep -inE "acknowledg|our (platform|service|company)" *.tex   # textual / platform leaks
pdftotext paper.pdf - | grep -icE "tuned|grid search|equal budget"  # baseline tuning stated?
pdftotext paper.pdf - | grep -icE "temporal split|leave-one-last"   # leakage-aware split?

Format anchors

  • RecSys uses the ACM two-column proceedings template; dense ranking tables and multi-panel offline/online figures overflow columns fast, so compress early rather than on deadline night.
  • The page counts above describe the 2026 cycle; treat every number as provisional and recheck the current Call for Contributions before relying on it.

Output format

[RecSys readiness] Ready / Needs fixes / Wrong track / Not ready
[Track] main-long / main-short / past-present-future / reproducibility / industry / resource / R&P-note
[Budget check] <pages used>/<budget>, appendix-inside-budget confirmed yes-no
[Anonymity risks] <logs / platform / deployed name / repository owner / metadata>
[Evidence risk] <baseline tuning / split leakage / offline-only claim>
[Fix order] <ordered blocking fixes>
Info
Name recsys-submission
Version v20260724
Size 5.7KB
Updated At 2026-07-29
Language