SIGIR prose has a recognizable register: it names the retrieval task before the model, quantifies on named collections with named metrics, and calibrates every adjective to a statistical test. Papers written in general-ML register ("we achieve state-of-the-art performance across diverse benchmarks") read as tourists. This skill converts drafts into the native register.
Reviewers form the accept/reject prior on page one. The arc that works:
Register conversion (before -> after)
-------------------------------------
"Our novel framework significantly outperforms strong baselines."
->
"On MS MARCO dev and TREC DL 2019/2020, OURS improves nDCG@10 over a
tuned BM25+monoT5 pipeline by 2.1-3.4 points (paired t-test, p<0.05,
Bonferroni-corrected across collections), at equal re-ranking depth."
"Experiments demonstrate the effectiveness and efficiency of our approach."
->
"OURS matches ColBERT-style quality within 0.4 nDCG@10 while storing
12x fewer vectors per document (Table 4); §5.3 isolates the pruning
step as the source of the storage saving."
| Say | Only if | Otherwise say |
|---|---|---|
| "significantly better" | A named test with correction passed | "better" / "numerically higher" |
| "state of the art" | Verified against the current published best on that collection + setup | "competitive with recent systems" |
| "generalizes" | ≥2 materially different collections/tasks tested | "transfers to |
| "efficient" | A cost table exists (latency/memory/index size) | Drop the word |
| "robust" | A stress condition was varied and reported | "stable across |
"Significant" is a reserved word in IR writing. Using it decoratively — while the community's own methodology papers police exactly this — is the fastest credibility leak available.
SIGIR argumentation is table-centric; prose narrates tables rather than replacing them. Conventions reviewers expect:
A load-bearing skeleton for a full paper (adjust, don't worship): intro (1),
related work (0.75), method (2), experimental setup (1.25), results + ablations
(2.5), analysis (1), limitations + conclusion (0.5). Appendices count inside the
budget at SIGIR, so this skeleton has no "we'll appendix it" release valve — the
repository is the release valve (see sigir-supplementary).
Short papers invert the proportions: setup and the single result table dominate; related work compresses to positioning sentences with dense citations.
SIGIR abstracts run dense and factual: task, failure, move, lineup, deltas, qualifier — typically 150-220 words with at least one number. If your abstract has no collection name and no metric by word 100, it is still in ML register. The final sentence belongs to availability ("code and run files at ...") or to the scope qualifier, not to a vision statement.
[Register diagnosis] native-IR / mixed / ML-tourist
[First-page arc] task-regime / failure / move / calibrated-evidence / bullets: present-missing each
[Reserved-word violations] "significant(ly)" uses without a test: <n>, lines <...>
[Table conventions] cutoffs / markers / bold-policy / caption-tests: pass-fail each
[Compression debt] <pages over budget> and the demotion plan
[Three worst sentences] <quoted, with rewrites>