EACL Writing Style

Use this to revise an EACL paper so its contribution is legible fast and its claims are scoped. EACL reviewers read many papers in a short window; the ones that land put the task and the result on the first page, quantify rather than assert, and name their limits. Pair this with the worked example in ../../resources/worked-examples/01-introduction.md.

The EACL first-page arc

1. Task — the specific problem, in the first breath, not "great progress in NLP."
2. Gap — why current methods fall short, each reason nameable.
3. What we do — the contribution, stated plainly.
4. Measured result — a number tied to a table, with variance.
5. Honest scope — what the result does and does not cover.

Habits to cut, habits to keep

Cut	Keep
"Achieves strong performance"	"Improves F1 by X (95% CI ...) over baseline B"
Generic "prior work is limited"	A specific failure per cited approach
A concrete example only on page 5	A worked example on page 1
Unscoped "our method generalizes"	"On the six languages tested; see Limitations"
Roadmap standing in for an argument	A one-line roadmap after the argument

Scope the LLM-era claim

• If the paper uses or evaluates LLMs, bound the claim to the models, prompts, and settings tested, and disclose contamination risk. An unscoped "LLMs can/cannot do X" invites the reviewer to name the counterexample.
• Report prompts and decoding as part of the method, not as trivia (see eacl-reproducibility).

Quantify the error analysis

• A page-one or early-section error analysis with counts ("40% of errors are agreement errors; examples in Table 3") is worth more than adjectives. EACL rewards papers that show where and why a system fails, especially across languages.

Anonymity-safe voice

Anonymity check before submission:
  - no author names, affiliations, or acknowledgements
  - no "as we showed in our EMNLP 2025 paper" -> use third-person citation
  - no links that identify authors (personal repos, named grant pages)
  - self-citations phrased neutrally

Multilingual clarity

• Name languages and scripts explicitly; render diacritics correctly in the PDF and later in the Anthology metadata (eacl-camera-ready).
• Do not let an aggregate multilingual score stand in for per-language honesty — a table beats an average.

Compression discipline

• The content pages carry the argument; appendices carry detail. If cutting for length pushes a core claim into an appendix, cut something else instead (see eacl-supplementary).
• The Limitations section is free space and read — use it to state scope, not to hide results.

Output format

[First-page arc] Present / Missing elements: <task/gap/what/result/scope>
[Overclaims] <phrases to scope, with fix>
[Evidence pairing] <claims lacking a table/number>
[Anonymity] <any leak>
[Multilingual honesty] <aggregate-hiding issues>
[Compression] <what to cut so the body carries the claim>