Skills

Acl Supplementary

Use when organizing appendices and supplementary material for an ACL paper under ACL...

Install

npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acl-supplementary -g -a claude-code -y
Category
Engineering
Updated
1mo ago
License
MIT
Context cost
Lightabout 1,400 tokens
Runs scripts
No, instructions only

What it does

Use when organizing appendices and supplementary material for an ACL paper under ACL Rolling Review, covering the mandatory Limitations and optional ethics sections, appendices after references, anonymized software and data archives, the no-cloud-links rule, and deciding what must stay in the 8-page or 4-page body.

ACL Supplementary

Use this when splitting an ACL paper between body, appendix, and archive. The governing ARR principle: reviewers are not required to consider material in appendices or supplements, so anything decision-critical that lives only there is effectively invisible.

The ACL page anatomy

[ content pages: 8 long / 4 short ]   <- the reviewed argument lives here
[ Limitations (REQUIRED, unlimited) ] <- after conclusion, outside page count
[ Ethics statement (optional) ]
[ References (unlimited) ]
[ Appendices (unlimited, same PDF) ]  <- optional reading for reviewers
+ separate .tgz/.zip archive          <- software / data supplement

Missing Limitations is a desk-reject condition; treating it as one throwaway sentence is a review-stage penalty even when it passes the gate.

What must not leave the body

  • The main results table and the headline comparison.
  • Task definition and enough of the method that a reviewer can judge novelty.
  • At least a summary of the error analysis, a pointer-only error analysis reads as not having one.
  • Human-evaluation design in one paragraph: raters, items, agreement.
  • The experimental setup at reproduction-outline level; full grids can go down.

What appendices are good at

  • Full prompt texts and few-shot exemplars (reference them per experiment).
  • Complete hyperparameter tables and search ranges.
  • Per-language / per-dataset breakdowns behind an averaged headline number.
  • Annotation guidelines and interface screenshots.
  • Extended qualitative examples and additional ablations.
  • Proofs or derivations for the occasional formal result.

Limitations section that actually works

Read the whole SKILL.md on GitHub

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