kdd-skills

Plugin kdd-skills from marketplace awesome-journal-skills in brycewang-stanford/Awesome-Journal-Skills. Commands read from the repo's manifest — 1 month ago.

Skills (12)

• kdd-artifact-evaluation

  Use when packaging code, datasets, configs, and deployment evidence for a KDD paper, where the repository cited in the submission is the only artifact reviewers can reach because rebuttals ban links. Covers anonymized repo construction, scale-claim harnesses, ADS evidence without production data, an

• kdd-author-response

  Use when drafting KDD rebuttals on OpenReview, where authors answer each review under a no-hyperlink rule, cannot upload revisions, and write for the area chair who recommends Accept, Reject, or Resubmit. Covers evidence-anchoring without links, per-reviewer triage, and turning a likely Resubmit int

• kdd-camera-ready

  Use when preparing an accepted KDD paper for ACM proceedings, covering the 12-page proceedings budget with 9 content pages, the extra content page over the submission, the 3-page cap on references plus appendix, ACM e-rights and TAPS source processing, ACM Open APC status, de-anonymization, and Digi

• kdd-experiments

  Use when designing or auditing the empirical section of a KDD paper, where evidence combines quality deltas with scalability and efficiency measurements, temporal-leakage-safe splits, mechanism-isolating ablations, tuning-symmetric baselines, and, for the ADS track, post-launch measurement design th

• kdd-related-work

  Use when positioning a KDD submission against the data-mining lineage (prior KDD volumes, ICDM, SDM, WSDM, CIKM, WWW) and the ML flagships, handling venue misattribution traps, cross-cycle resubmission overlap, concurrent arXiv work, and the mechanism-contrast style of novelty argument that ACM SIGK

• kdd-reproducibility

  Use when hardening the reproducibility story of a KDD paper, where reproducibility is an explicit decision factor for area chairs. Covers claim-to-evidence tiers for mining pipelines, seeds and splits on large graphs and streams, baseline-tuning disclosure, compute reporting, and honest limits for A

• kdd-review-process

  Use when reasoning about how KDD papers get judged in its dual-cycle OpenReview process: per-review rebuttal, area-chair recommendations weighed on merit through reproducibility and ethics, PC-chair decisions, the Resubmit outcome feeding the next cycle, the mixed academic-industry reviewer pool, an

• kdd-submission

  Use when auditing a KDD submission for readiness in either cycle, covering Research vs ADS track declaration, OpenReview profile completeness for all authors, the ACM sigconf 8-content-page budget, double-blind checks, in-paper artifact references, resubmission declarations, and desk-reject triggers

• kdd-supplementary

  Use when splitting a KDD paper across its 8 content pages, the optional appendix after the references, and the cited repository, under the camera-ready rule capping references plus appendix at 3 of 12 pages. Covers appendix triage, reviewer-discretion reality, and the one-page cross-cycle resubmissi

• kdd-topic-selection

  Use when deciding whether a project belongs at KDD and in which track — Research vs Applied Data Science vs Datasets and Benchmarks vs AI for Sciences — or whether it routes to ICDM, SDM, WSDM, CIKM, WWW, VLDB, or an ML flagship. Covers the deployment-evidence fork, data-regime framing, and SIGKDD f

• kdd-workflow

  Use when planning a KDD project calendar across the venue's two submission cycles per year, including cycle choice, abstract-then-paper deadline pairs a week apart, rebuttal capacity planning, the Resubmit-to-next-cycle loop, ADS evidence lead times, and ACM e-rights/TAPS camera-ready scheduling for

• kdd-writing-style

  Use when revising a KDD paper into the venue's register, where the first page names a data regime, a mechanism, and scale evidence, efficiency adjectives trace to design decisions, and two-column sigconf pages punish sprawl. Covers Research vs ADS voice, dataset-size discipline, assertive contributi

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