Skill UI

A comprehensive guide for authors submitting to machine learning conferences like NeurIPS. It details the rigorous standards for data splitting, hyperparameter reporting, random-seed protocols, and compute transparency required for a main-track paper. It also helps authors strategically decide between the main track and the MLRC/TMLR routes based on their core contribution (replication vs. novelty).

A specialized guide for authors preparing manuscripts for top-tier academic journals. This skill teaches how to structure and write the mandatory contribution statement (under 500 words), focusing on articulating the paper's overall contribution to the field rather than simply claiming novelty. It covers identifying the source of contribution (e.g., new data, mechanism, theory) and aligning the discussion section to match the high-stakes claim made in the statement.

This guide helps researchers determine if their problem constitutes a rigorous Operations Research (OR) or Management Science (MS) methodological contribution. It provides a comprehensive fit test covering method novelty, mathematical rigor (proofs, guarantees), and significance to the OR community. Furthermore, it guides users on selecting the precise editorial area (e.g., Optimization, Stochastic Models, Simulation) for submission.

A comprehensive guide for researchers positioning academic work within the pervasive and ubiquitous computing literature (e.g., PerCom, MobiCom). It teaches the critical 'delta-first' method, instructing authors to highlight their unique contribution and novelty contrast against the nearest prior work, rather than simply listing citations. Essential for proving field command and eligibility.

A comprehensive guide for authors considering Physical Review E (PRE) as a target venue. It details the journal's scope in statistical, nonlinear, and soft-matter physics, emphasizing methodological rigor over headline novelty. Use this skill to assess if your manuscript meets the required standards for completeness, reproducibility, and technical depth before submission.

This guide details the rigorous and single-shot review process for ACM's Principles of Distributed Computing (PODC). Unlike venues with major revision rounds, PODC focuses entirely on the strength of the proof, the significance of the result, and the honesty of the model. It outlines the criteria (correctness, novelty, tightness) and emphasizes that all necessary work must be completed pre-submission, as there are no post-acceptance revision cycles.

A comprehensive guide for positioning Operations Research manuscripts within the Production and Operations Management (POM) academic landscape. It helps authors compare their work against canonical departmental literature, adjacent top-tier journals (e.g., M&SOM, OR), and rigorously define axes of novelty (setting, mechanism, method). Useful when determining the optimal venue or clarifying the paper's unique contribution.

This guide provides strict guidelines for authors writing the "Related Work" section for top-tier programming language theory conferences like POPL. It emphasizes moving beyond general literature reviews to pinpoint precise, technical "delta sentences" that prove novelty against neighboring formal systems. It covers citation standards, venue mapping, and attribution verification for maximum academic impact.

This guide details the complete academic lifecycle for a paper submitted to the POPL conference, culminating in a journal issue. It covers all critical stages: double-blind review, handling author responses, navigating conditional acceptance, mandatory revisions, and understanding how academic rigor (correctness, novelty, significance) is assessed by the committee. Essential reading for researchers.

This guide teaches how to structure the "Related Work" section for top-tier AI journals, focusing on demonstrating the novel incremental contribution (delta) rather than simply listing existing literature. It covers positioning the work within ML/CV/NLP, defining novel problem dimensions, and structuring rigorous comparison tables to withstand external review scrutiny.

A comprehensive guide for structuring the Related Work section for top-tier recommender systems conferences (RecSys). It advises authors on auditing novelty by positioning their contribution against adjacent research fields (e.g., SIGIR, KDD, WSDM), addressing critical lines (like reproducibility and off-policy evaluation), and ensuring the work is technically distinct from prior or concurrent studies.

A comprehensive guide to the rigorous academic peer review process, exemplified by top-tier Recommender Systems conferences (RecSys). It details the double-blind review mechanics, key evaluation criteria (novelty, validity, reproducibility), the critical rebuttal phase, and the requirements for final publication in ACM Digital Library. Essential for researchers and students aiming to improve academic submission quality.