# Acl Artifact Evaluation

Use when packaging code, datasets, prompts, model outputs, or annotation materials for...

- Repository: https://github.com/brycewang-stanford/Awesome-Journal-Skills (1346 stars)
- Category: Data and ML
- License: MIT
- Last updated: 2026-09-27
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acl-artifact-evaluation -g -a claude-code -y`
Codex: `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acl-artifact-evaluation -g -a codex -y`
Cursor: `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acl-artifact-evaluation -g -a cursor -y`
Gemini CLI: `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill acl-artifact-evaluation -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add brycewang-stanford/Awesome-Journal-Skills`

## Description

Use when packaging code, datasets, prompts, model outputs, or annotation materials for an ACL submission under ACL Rolling Review, covering anonymized supplement archives, scientific-artifact items of the Responsible NLP checklist, licensing and intended-use documentation, data statements, and post-acceptance public release.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# ACL Artifact Evaluation

Use this to plan the evidence package around an ACL paper. ACL has no separate
artifact-badge track; instead, artifact scrutiny is folded into review through
the supplement archive and Section B ("scientific artifacts") of the
Responsible NLP checklist, which reviewers cross-check against the PDF.

## What counts as an artifact here

- Code: training/inference scripts, evaluation harnesses, prompt templates.
- Data: new corpora, annotations, filtered subsets of existing corpora, test
  suites, adversarial sets.
- Model outputs: generations, ranked lists, logits used in analysis, often the
  cheapest way to make an LLM paper checkable without GPUs.
- Human-subject materials: annotation guidelines, interface screenshots,
  consent text, compensation description.

## Submission-time packaging rules

- Supplements upload as .tgz/.zip through the OpenReview form; links to
  tracked cloud storage are not acceptable, and any linked page must be
  anonymous.
- Scrub identity everywhere reviewers can look: file paths, git metadata,
  notebook author fields, license headers, dataset hosting pages, README
  contact lines.
- Reviewers are not required to open supplements. The paper plus checklist
  must stand alone; the archive is for verification, not for essential content.

## Checklist items your artifact must satisfy

The rest: https://github.com/brycewang-stanford/Awesome-Journal-Skills/blob/HEAD/ACL-Skills/skills/acl-artifact-evaluation/SKILL.md