emnlp-skills

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

Skills (12)

• emnlp-artifact-evaluation

  Use when packaging the artifacts of an EMNLP paper — datasets, annotation guidelines, prompts, evaluation code, and model outputs — as anonymous review-time evidence or public post-acceptance releases, with licensing, data statements, and the inspection order NLP reviewers actually follow.

• emnlp-author-response

  Use when drafting an EMNLP author response in the ACL Rolling Review discussion window — triaging replies by soundness versus excitement, deciding what evidence can be added mid-review, staying anonymous, and writing for the area chair's meta-review and the post-commitment Senior Area Chairs, not th

• emnlp-camera-ready

  Use when converting an accepted EMNLP paper — Main or Findings — into its ACL Anthology camera-ready form: de-anonymization, integrating response-phase commitments, Limitations and checklist-appendix handling, Anthology metadata hygiene, artifact link restoration, and Budapest presentation and regis

• emnlp-experiments

  Use when designing or auditing the experimental program of an EMNLP paper — baseline fairness and tuning budgets, dataset and language coverage matched to claims, contamination audits for pretrained and API models, significance testing and seed variance, human evaluation protocols, prompt sensitivit

• emnlp-related-work

  Use when positioning an EMNLP submission inside NLP's fast-moving literature — covering ACL Anthology lineages and arXiv concurrency, citing Findings and workshop papers correctly, tracing dataset and benchmark ancestry, verifying every reference resolves under the hallucinated-citation policy, and

• emnlp-reproducibility

  Use when hardening an EMNLP paper's reproducibility record — answering the Responsible NLP checklist truthfully under desk-reject enforcement, pinning model versions and API snapshot dates, logging decoding parameters and prompts, documenting data licensing and annotation, and reporting compute so a

• emnlp-review-process

  Use when explaining or strategizing around EMNLP's two-stage pipeline — ACL Rolling Review scoring with soundness, excitement, and overall recommendation, area-chair meta-reviews, the commitment step, and conference-side decisions by Senior Area Chairs into Main, Findings, or rejection — including r

• emnlp-submission

  Use when auditing an EMNLP submission before the ACL Rolling Review deadline, covering ACL-template compliance, the 8-page long / 4-page short caps, the mandatory Limitations section, the Responsible NLP checklist and its desk-reject enforcement, anonymization without an anonymity period, venue pref

• emnlp-supplementary

  Use when dividing an EMNLP paper between content pages, uncounted Limitations and ethics sections, appendices, and ACL Rolling Review supplementary uploads — deciding what reviewers are owed in the body, what belongs in appendix prompts-and-tables territory, and what ships as anonymous code and data

• emnlp-topic-selection

  Use when deciding whether a project belongs at EMNLP, weighing its empirical-NLP identity against ACL, NAACL, EACL, AACL, CoNLL, LREC-COLING, TACL, and ML venues, matching the contribution to EMNLP's welcomed paper types including negative results and reproductions, and choosing between main confere

• emnlp-workflow

  Use when planning an EMNLP project calendar end to end — choosing the ACL Rolling Review cycle that feeds the conference, backward-planning experiments and annotation to the ARR deadline, scheduling the author response window, deciding commit versus revise-and-resubmit, and mapping camera-ready and

• emnlp-writing-style

  Use when revising an EMNLP draft for the venue's empirical voice — phenomenon-first framing, claims scoped to tested languages and domains, examples tied to counted errors, a Limitations section with content, honest hedging calibrated to evidence strength, and ACL two-column discipline for long and

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