Skill UI

A comprehensive guide for revising NLP and Computational Linguistics manuscripts for submission to top-tier conferences like ACL. It mandates adopting a task-first, evidence-grounded approach, strictly scoping claims in the LLM era, and ensuring linguistic rigor in all examples and analyses. Learn how to structure, compress, and refine your arguments for maximum impact.

This guide outlines best practices for authors presenting theoretical and empirical results for top-tier journals like the American Economic Journal: Microeconomics (AEJ: Micro). It covers structuring propositions, building transparent numerical examples, creating schematic figures, and formatting tables (including mandated use of standard errors over significance asterisks) to ensure maximum clarity and adherence to academic publishing standards.

A comprehensive guide detailing the empirical writing style required for EMNLP submissions. It emphasizes scoping claims to specific datasets and languages, ensuring examples are load-bearing, structuring the argument phenomenon-first, and accurately calibrating hedging language based on evidence strength.

Provides rigorous guidelines for analyzing experimental game data and constructing numerical examples for high-level theoretical journals. Emphasizes that analysis must be tightly linked to theoretical claims, such as matching observed outcomes to predicted equilibria, rather than serving as general causal evidence. Covers session-level clustering, structural fitting, and ensuring computational reproducibility.

A guide for authors submitting to theoretical computer science venues (ITCS). It strictly defines what constitutes valid evidence for a mathematical claim, emphasizing that complete proofs are paramount. The guidelines detail how to use worked examples, separating objects, and appropriately scoped computations, while strongly advising against using empirical benchmarks or performance metrics.

This guide provides strict guidelines for authors submitting highly theoretical papers (e.g., to Journal of Economic Theory) regarding computational, numerical, or empirical evidence. It enforces the 'theory-first' principle, ensuring that all quantitative work—including simulations, examples, and counterexamples—must serve to illustrate, test, or deepen the main theoretical contribution, rather than standing as a standalone finding. Key requirements include maintaining reproducibility, keeping examples minimal, and proper structural placement.

Provides comprehensive guidelines for authors submitting to the Journal of Economic Theory (JET). It details mandatory data sharing (Elsevier Option C), ensuring computational reproducibility for numerical examples, and proper declaration of generative AI usage. This playbook helps authors structure their submissions to meet high academic standards of verifiable evidence and transparency.

Prepares datasets, code, glossed corpora, and sound files for a Language (LSA) manuscript. Covers reproducible quantitative pipelines, Leipzig-glossed fieldwork examples, phonetic scripts, community consent and anonymization ethics, and data-availability statements.

Prepares exhibits for linguistics manuscripts including numbered examples, interlinear glosses, IPA transcription, and quantitative tables. Ensures compliance with Language journal conventions like Leipzig Glossing Rules. Formats syntactic trees and figures for double-anonymous review. Does not generate data but structures existing linguistic evidence.

A comprehensive guide for revising technical submissions, particularly in computational linguistics and NLP. It details how to enforce linguistic scope discipline, present examples as verifiable arguments, structure the first page for maximum impact, anticipate reviewer limitations, and maintain strict terminology consistency for high-stakes academic publishing.

A comprehensive guide for authors aiming to submit top-tier technical papers (like those for OOPSLA). It teaches how to transform descriptive drafts into highly verifiable, structured academic arguments. Focus areas include developing running examples, articulating falsifiable claims, optimizing article pacing, and anticipating reviewer challenges to maximize the chances of acceptance.

A comprehensive guide for structuring and refining high-quality database systems research papers for top-tier conferences like SIGMOD. It covers essential components such as establishing a clear page-one contract, integrating running examples, scoping measured system claims, adopting third-person voice, and adhering to the 12-page ACM template structure for maximum technical impact.