Skill UI

This guide provides advanced strategies for authors to position their research contribution within the broader academic debate, particularly for highly competitive, generalist journals like APSR. It teaches authors how to move beyond subfield-specific citations by identifying the core contested debate, engaging cross-subfield literature, and framing the paper's move to ensure its relevance to a general political science audience.

This guide provides a detailed strategy for responding to a Revise-and-Resubmit (R&R) decision for high-stakes academic journals. It teaches authors how to structure a persuasive cover letter, address conflicting reviewer demands, and reconcile feedback without weakening the paper's core contribution. Focuses on maintaining scholarly rigor and managing editor expectations.

This tool serves as the central entry point and orchestrator for drafting an American Political Science Review (APSR) manuscript. It guides authors through the complex academic publishing lifecycle by determining the paper's specific track (e.g., Regular Article, Synthesis, Registered Report) and its current developmental stage (e.g., Idea, Theory, Data Analysis). It does not draft content; rather, it routes the user to the most relevant sub-skill for the next step in the writing process.

This guide outlines a systematic methodology for conducting comprehensive literature reviews in economics. It moves beyond simple summarizing by teaching researchers how to build an evidence matrix, ensuring systematic coverage by sweeping databases (JEL codes, keywords, working papers). It is essential for preparing high-impact academic reviews that must prove exhaustive coverage and synthesize complex, often conflicting, findings.

A comprehensive guide for authors preparing manuscripts for the International Conference on Artificial Intelligence and Statistics (AISTATS). It advises on whether the paper's contribution is statistically grounded and theory-backed, guiding framing, evidence presentation, and understanding reviewer expectations in statistical machine learning.

This guide details the mandatory steps for preparing the final, camera-ready version of an ASE conference paper. It covers systematic de-anonymization (restoring real author details, tools, and grants), utilizing the extra content page for incorporating review feedback, finalizing permanent DOI-archived data availability statements, and ensuring strict adherence to mandated dual IEEE/ACM templates and metadata requirements.

A detailed guide for authors writing the Related Work section of an Automated Software Engineering (ASE) paper. It teaches the crucial 'delta argument' methodology, emphasizing that positioning must be against prior automated tools, covering multiple SE literature lanes, and conducting fair, head-to-head empirical comparisons to clearly delineate the novelty of the proposed work.

A comprehensive audit guide for submitting research papers to IEEE/ACM ASE conferences. It covers strict formatting rules (acmart template, page budget), mandatory Data Availability Statements, double-anonymous review compliance, and critical submission pitfalls like identity leaks and template errors. Use this checklist before uploading to HotCRP to maximize acceptance chances.

This guide outlines the critical rules for structuring technical research papers submitted to top-tier conferences like ASE. It emphasizes the 'decision-criticality' rule, instructing authors on how to separate core arguments (which must fit within the 10-page body) from reproduction details, raw logs, and supplementary material (the artifact). Mastering this separation is crucial for ensuring reviewers judge the paper on its merits, not its supplementary data.

Provides comprehensive guidelines for structuring and writing academic papers for Automated Software Engineering (ASE) conferences. It teaches authors how to present an automated task, emphasize the automation design over the deep learning model, provide evidence from real subjects, and adhere to strict formatting and argument presentation rules to maximize acceptance chances.

A comprehensive guide for authors aiming to submit machine learning manuscripts to the Asian Conference on Machine Learning (ACML). This skill helps evaluate manuscript fit, re-frame research from journal or arXiv styles, understand required contribution types (e.g., algorithms, theorems, benchmarks), and align the paper's evidence bar with the expectations of a top-tier, regional AI/ML venue. Use it for venue selection and submission strategy development.

This guide provides a tactical framework for drafting high-stakes author responses (rebuttals) to peer reviews in top-tier academic conferences. It details how to triage reviewer comments (factual errors, questions, disputes), structure the argument within strict word limits (e.g., 800 words), and maintain a professional, evidence-based tone to maximize the paper's chances of acceptance or major revision.