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
text[ 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
| Weak pattern | Stronger ACL pattern |
|---|---|
| "Results may not generalize" | Name the languages, domains, and model scales actually tested and the nearest untested regime |
| "LLMs can hallucinate" | State which conclusions depend on a specific model snapshot and API behavior |
| Silent on data | Note license constraints, demographic skew, or collection-window bias in the corpora used |
| Written last-minute | Mirrors the risks reviewers will find anyway, defusing them on your terms |
ACL's policy explicitly instructs reviewers not to punish honest limitations, which makes this section the cheapest goodwill in the whole submission.
Archive rules and hygiene
- Upload software/data as .tgz or .zip in the OpenReview fields; personal cloud-storage links are barred, and any external page must be anonymous and untracked.
- Strip authorship trails: git history, notebook metadata, absolute paths with usernames, license headers, README contact lines.
- Test the archive on a clean machine: it must unpack, the README must state what maps to which table, and nothing should require credentials just to read.
- Include model outputs where feasible so reviewers can verify scoring without
compute (see
acl-reproducibility).
Body-vs-appendix vignette
A long paper introduces a retrieval-augmented QA method with results on six benchmarks in three languages. Body: method figure, main table (six benchmarks averaged + per-language block), two-paragraph error analysis, one ablation that carries the mechanism claim. Appendix: full per-benchmark tables, prompts, retrieval index details, remaining ablations, annotation guidelines for the human study. Archive: code, prompts as files, and all model outputs. The test: a reviewer who never scrolls past the references can still reconstruct and believe every claim in the abstract.
Appendix ordering convention that reviewers navigate well
- A: full experimental setup (models, hyperparameters, hardware, budgets).
- B: prompts and few-shot exemplars, one subsection per experiment.
- C: complete results — per-dataset, per-language, per-seed tables behind every averaged number in the body.
- D: annotation materials — guidelines, interface, pay, agreement detail.
- E: additional analyses and ablations, each forward-referenced from the body at least once (unreferenced appendix content is invisible).
- F: qualitative examples, marked as random or curated — say which.
Number tables and figures continuously with the body so the author response can cite "Table 9" unambiguously during the discussion phase.
Ethics statement: when to write one
Write it when the paper involves human subjects or annotators, scraped user-generated content, demographic inference, dual-use capability, or release of models/data with realistic misuse paths. Skip it when nothing applies — the Responsible NLP checklist already covers the routine cases, and a padded statement invites the very scrutiny it fails to answer. It shares the unlimited space after the conclusion with Limitations.
Size and dependency guardrails
- Keep the archive small enough to download on conference-hotel wifi; reviewers abandon multi-gigabyte supplements unopened.
- No credentials, no API keys, no gated-model weights — describe access paths instead of shipping secrets.
- Pin dependency versions in one environment file; "latest transformers" is a different codebase every cycle.
- If data cannot be shared (license, privacy), include the loader code and a synthetic sample with identical schema so scripts still run.
Output format
text[Split status] sound / body-overloaded / appendix-dependent [Limitations quality] substantive / ritual / missing [Must-move-up] <decision-critical items currently below the fold> [Archive check] <format/anonymity/clean-machine findings> [Reviewer-blind spots] <claims visible only outside the body>
