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 conference, Findings, industry, and demo pipelines.
Profile →npx skills add brycewang-stanford/Awesome-Journal-Skills --skill emnlp-topic-selection --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# EMNLP Topic Selection Use this before writing. EMNLP's name is its thesis: *empirical methods*. The venue's center of gravity is work whose contribution is established by measurement — new evaluations, datasets, analyses of model behavior, and methods whose value is demonstrated rather than argued. Sibling venues share the reviewer pool through ARR, so the routing question is less "will it be reviewed differently" than "which program will want it." ## The empirical-identity test Ask three questions of the project: 1. **Is there a language phenomenon or task behavior at the center?** EMNLP papers are about something a system does with language, not about an architecture that happens to be evaluated on text. 2. **Does the evidence plan include analysis, not just scores?** The venue's reviewing culture expects error analysis, ablations that isolate the mechanism, and claims scoped to the languages and domains actually tested. 3. **Would the paper survive its own evaluation section being adversarial?** Benchmarks chosen to flatter, contaminated test sets, and single-run comparisons are the fingerprints reviewers here are trained to find. Three yeses: EMNLP-shaped. A no on (1) suggest
- The empirical-identity test
- Welcomed contribution types
- Routing among the siblings
- One project, three honest pitches
- Timing as a fit dimension
- Findings in the fit calculus
- The re-route that saves a cycle
- Output format
What does the emnlp-topic-selection skill do?
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 conference, Findings, industry, and demo pipelines.
How do I install it?
Run `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill emnlp-topic-selection --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From brycewang-stanford/Awesome-Journal-Skills, a repository with 984 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.