Skill UI

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 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 addressing the rebuttal window for major NLP/AI conferences (like EACL). It details how to strategically triage reviewer objections, craft responses for both individual reviewers and the action editor's meta-review, plan runnable in-window experiments, and make critical decisions about the paper's future venue.

This guide details the critical process of transforming an accepted, anonymous conference paper into its final, published, open-access version for the ACL Anthology. It covers the essential 'three-source merge' process: integrating reviewer-promised revisions, restoring author identity and community acknowledgements, correcting metadata, and managing conference logistics. Essential reading for authors submitting to top-tier NLP venues like NAACL.

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.