SIGIR Academic Writing Style
Refines academic research drafts into the rigorous, table-centric native writing register required for ACM SIGIR conference submissions.
The SIGIR Academic Writing Style skill assists researchers and computer scientists in converting generic machine learning drafts into publication-ready Information Retrieval (IR) conference papers. It enforces the specific structural and linguistic conventions of ACM SIGIR, such as leading with explicit retrieval tasks, datasets, and cutoff metrics, strictly calibrating statistical claim sentences, formatting dense tabular results with rigorous significance testing annotations, and fitting full papers into the strict 9-page limit without compromising scientific soundness.
Características Principales
01Converts general machine learning prose into precise, task-first Information Retrieval register
02Calibrates scientific claims and restricts decorative vocabulary like 'significant' to verified tests
03Structures the critical first-page arc with mechanism-first problem definitions and checkable contributions
04Enforces SIGIR-standard table formatting with explicit metric cutoffs, baseline groupings, and statistical markers
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06Provides a 5-pass revision protocol to optimize 9-page conference budget allocations without removing essential protocol details
Casos de Uso
01Auditing draft manuscripts for unsupported claim adjectives and uncalibrated statistical significance statements
02Compressing overflowing retrieval paper drafts into the strict 9-page conference page budget
03Drafting or restructuring the introduction and abstract for an ACM SIGIR full or short research paper