Skill UI

A comprehensive guide for academic researchers aiming to submit papers to the top accounting journal, *Accounting Research*. This skill helps authors identify if their research focus aligns with core accounting mechanisms, such as disclosure quality, auditing standards, and regulatory changes, distinguishing it from general corporate finance or economics.

This skill provides comprehensive guidance for authors submitting to Accounts of Chemical Research (ACS). It helps researchers understand the journal's unique niche: publishing concise, first-person, narrative accounts of a research program's evolution, rather than comprehensive field reviews or primary data reports. It serves as a fit-checking tool, guiding manuscript framing, required evidence, and house style.

A comprehensive guide for packaging and submitting evidence packages (artifacts) for NLP research papers, such as code, datasets, prompts, and model outputs. It details requirements for reproducibility, adhering to the Responsible NLP checklist, ensuring proper anonymization, and preparing for post-acceptance public release in academic settings like ACL.

A comprehensive guide for authors on drafting a strategic response during the OpenReview cycle. This resource covers how to address reviewer objections, shape the Area Chair's meta-review summary, manage the discussion phase, and decide whether to defend the paper or withdraw for a future revision cycle. Focus on clarity, conciseness, and evidence-based arguments.

This comprehensive guide outlines the meticulous workflow for preparing a research paper for final publication (Camera-Ready) after acceptance at major NLP conferences like ACL. It covers critical steps including de-anonymization (restoring author details and acknowledgements), integrating mandates from meta-reviews, adding required disclosures (e.g., funding, AI assistance), and ensuring all technical metadata, font embedding, and licensing comply with the permanent open-access standards of the ACL Anthology.

A comprehensive guide for researchers designing and auditing NLP experiments for top-tier conferences. It covers establishing defensible baselines, ensuring evaluation breadth, performing rigorous statistical tests (significance, variance), controlling for data contamination, and structuring detailed functional error analysis. Essential reading for publishing reliable AI research.

This comprehensive guide provides expert strategies for structuring and auditing the "Related Work" section for top-tier NLP conferences (like ACL). It covers citation hygiene (Anthology vs. arXiv), maintaining temporal freshness against rapidly evolving baselines, and articulating clear technical contrasts to prove the novelty of your research. Essential for high-stakes academic publishing.

A comprehensive guide detailing the standards required for academic reproducibility in NLP and LLM research. It covers the 'Responsible NLP checklist' requirements, including detailed reporting for hyperparameters, model versions, exact prompts, decoding parameters, data contamination auditing, and variance reporting to ensure claims are auditable and robust.

A comprehensive guide to modeling the entire academic review cycle for major NLP conferences like ACL. It details the stages from initial submission (ARR cycle intake) through peer review, author response, meta-review synthesis, commitment decision, and final venue decision (Main Conference, Findings, or Reject). It also outlines the roles of reviewers, area chairs, and program chairs, providing strategic advice for authors on navigating the complex publication landscape.

A comprehensive audit checklist for authors submitting papers to major NLP conferences (like ACL) via OpenReview. This guide covers mandatory formatting rules, maintaining anonymity, addressing ethical declarations (Responsible NLP), managing resubmission links, and ensuring adherence to the entire submission workflow to prevent desk rejection.

A comprehensive guide for authors preparing submissions for ACL conferences. It details how to effectively split content across the main body, required Limitations section, optional Ethics statement, and supplementary archives. Learn best practices for ensuring critical findings remain visible to reviewers, maximizing reproducibility, and structuring appendices for maximum impact.

A comprehensive guide for NLP researchers on strategically positioning their work before writing. It teaches how to determine the core linguistic contribution, select the optimal academic venue (ACL, EMNLP, etc.), manage the scope (long vs. short papers), and align the research focus with specific conference themes and review expectations, maximizing publication impact.