Skill UI

A comprehensive guide detailing the rigorous, multi-stage workflow for submitting a research manuscript to a major conference like DAC. It covers backward planning from the final conference, emphasizing the critical two-stage submission (Abstract then Manuscript), and outlining deadlines for review, camera-ready submission, and post-acceptance procedures.

A comprehensive guide for authors drafting research manuscripts for the ACM/IEEE DAC conference. It teaches how to structure a deep, measurable contribution within a strict six-page, double-column format. Key principles include front-loading the contribution, stating results as a clear QoR delta (PPA), adhering to academic constraints (double-blind review, third-person citation), and prioritizing data tables over extensive background prose.

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 comprehensive guide outlines the critical steps required to prepare a camera-ready version of an NLP conference paper (e.g., EACL). It covers mandatory submissions after acceptance, including content expansion, de-anonymization (restoring author names, citations, and metadata), addressing meta-review required changes, ensuring correct ACL Anthology metadata, and managing public artifact release and presentation logistics. Essential for ensuring academic integrity and compliance.

This guide models the end-to-end review pipeline for EACL conference submissions. It details the stages—from initial ARR review and author rebuttals to the action editor's meta-review and final committee commitment. It provides strategic advice on interpreting outcomes (Main, Findings, Reject), handling ethical concerns, and planning re-routing to sibling ACL venues.

A comprehensive guide for authors preparing the single, short, double-blind rebuttal (Author Response) required during major AI conference review cycles (e.g., IJCAI-ECAI). It teaches authors how to precisely correct factual misreadings, supply missing evidence, and structure their arguments effectively within strict length limits, focusing only on verifiable facts rather than new claims or philosophical arguments.

This guide provides best practices for authors writing the Related Work section for top-tier AI conferences (e.g., ECAI). It instructs users on how to cover diverse AI lanes (symbolic, learning, multi-agent, application) for broad reviewers, employ 'Delta-first' positioning to state novelty concisely, and adhere to strict page budgets and double-blind review rules.

This guide models the comprehensive review pipeline for ECAI submissions, detailing the single-round, double-blind process. It covers the summary-reject phase, full review by area chairs, the single rebuttal window, and the final accept/reject decision. It contrasts this process with journal revisions and other major AI conferences (AAAI, IJCAI) to help authors strategize for submission success.

A comprehensive guide for authors submitting to major AI conferences (like ECAI). It teaches the critical skill of separating core, decision-critical arguments (must be in the main body) from supporting details, proofs, and code (which belong in the optional supplement). This ensures reviewers can fairly judge the contribution despite strict page limits.

This comprehensive guide outlines a detailed, backward-planning workflow for submitting research papers to major AI conferences like ECAI or IJCAI-ECAI. It covers the entire academic lifecycle, from initial topic selection and evidence type planning to abstract submission, full paper drafting, rebuttal response, and final camera-ready publication, ensuring authors meet strict deadlines and adhere to rigorous review standards.

This guide provides a detailed strategy for managing and releasing research artifacts (code, models, data) associated with a vision paper submitted to ECCV. It covers two critical phases: the sealed, anonymous archival submission during review, and the structured public release runway post-acceptance, ensuring reproducibility and adherence to conference policies.

A comprehensive guide for designing and auditing high-stakes computer vision experiments for top-tier conferences. It covers critical areas like 'matched-substrate fairness,' 'six-month-staleness testing,' and rigorous ablation studies, ensuring that claims are robust, reproducible, and withstand intense peer review scrutiny.