Skill UI

A comprehensive guide detailing how to manage the division of content between the core 7-page paper body and the supplemental materials package for SIGGRAPH submissions. It emphasizes treating the results video as primary evidence, providing best practices for video creation, comparison galleries, and organizing additional technical evidence (code, data, proofs).

This skill assists researchers in strategically positioning their computer graphics and visualization research. It evaluates whether a contribution is truly "graphics-shaped" (demanding visual results and advancing graphics axes) and recommends the optimal venue (e.g., SIGGRAPH, CVPR, CHI, EGSR) and submission track (Dual-track or Journal-only) based on the nature and maturity of the work. It provides a crucial, high-leverage decision framework before committing to a submission.

A detailed guide for managing the entire academic paper submission process for major graphics conferences like SIGGRAPH and SIGGRAPH Asia. It outlines the two annual cycles, backward planning from deadlines, key milestones (results video, baselines), rebuttal strategies, and final camera-ready submission steps, ensuring researchers can manage complex timelines effectively.

This comprehensive guide provides the optimal structure and academic writing discipline for submitting high-quality technical papers to major computer graphics conferences, such as SIGGRAPH. It emphasizes building a compelling 'first-page arc,' leveraging the teaser figure to immediately demonstrate results, maintaining academic honesty by detailing limitations, and adhering to strict page budget constraints.

A comprehensive guide for packaging and submitting artifacts for Information Retrieval (IR) conferences (like SIGIR). It details the strict requirements for reproducibility, including mandatory components like TREC-format run files, qrels, and index recipes. The process covers repository structure, anonymization for review, handling data provenance, and ensuring that results can be audited by any reviewer using standard community tooling.

This guide provides a comprehensive framework for authors responding to peer reviews in major NLP/IR conferences. It covers strategies for active rebuttal periods, pre-emptive revisions when no window exists, and planning resubmissions after rejection. Key advice includes technical rebuttal tactics (e.g., addressing baselines, significance testing), maintaining professional tone, and efficiently using existing computational evidence to maximize acceptance chances.

This guide details the critical steps and changes required to transform a reviewed SIGIR submission into the final Version of Record published via ACM Digital Library. It covers technical requirements, metadata standardization (CCS, keywords), conflict resolution, and adhering to publishing timelines and copyright protocols (e-rights, TAPS).

This comprehensive guide details the rigorous methodology for designing, executing, and reporting experimental results in Information Retrieval (IR). It covers best practices for selecting appropriate test collections, choosing defensible metrics, performing proper statistical significance testing (e.g., paired t-tests), ensuring baseline fairness, and proactively addressing modern pitfalls like LLM contamination. Essential for publishing high-quality, auditable research in IR/NLP.

A comprehensive guide on structuring the 'Related Work' section for top-tier Information Retrieval (IR) conferences (like SIGIR). Learn to trace the lineage of your research through canonical history (e.g., BM25, ColBERT), mechanically articulate your technical 'delta' (novel contribution), and avoid common pitfalls like venue misattribution and insufficient contrast.

A comprehensive guide for ensuring the reproducibility of Information Retrieval (IR) research, essential for SIGIR submissions. It details best practices for pinning data collection versions, index settings, neural model hyperparameters, and managing non-determinism. It helps researchers document artifacts—not just promises—to validate reported gains.

A detailed guide modeling the complex academic review machinery, using SIGIR as a primary example. It covers everything from per-track anonymity regimes and PC-member nomination duties to the critical scoring criteria: evaluating validity, fairness of comparison, and statistical rigor. Essential reading for authors preparing high-stakes research submissions.

A comprehensive audit checklist designed for authors submitting papers to the SIGIR conference. It guides users through critical pre-submission checks, covering adherence to specific full/short paper formats, mandatory anonymization techniques (e.g., stripping system names, log provenance), cross-track submission rules, AI disclosure requirements, and common pitfalls that lead to desk rejection.