Skill UI

This guide provides best practices for authors writing the "Related Work" section for interdisciplinary AI conferences. It teaches how to precisely position novelty across multiple domains—including ML fairness, law, HCI, and critical theory—by writing delta-first contrasts and properly attributing borrowed concepts to their original academic source.

This guide provides comprehensive best practices for writing the 'Related Work' section for submissions to top-tier storage conferences like FAST. It emphasizes adopting a 'delta-first' contrast approach, requiring authors to position their novelty against the entire spectrum of storage literature (including OSDI, SOSP, and dedicated workshops), rather than merely citing proximate works. It also covers handling concurrent submissions and maintaining double-blind anonymity.

A comprehensive guide for researchers deciding the optimal conference venue (e.g., FAST, OSDI, NSDI, ATC) for their storage-related academic work. It advises on distinguishing a core storage contribution from general systems results, detailing specific contribution shapes FAST rewards, and providing routing logic based on the project's nature and evidence maturity.

This guide offers advanced methodological advice for structuring the 'Related Work' section for top-tier theoretical computer science conferences (like FOCS). It teaches researchers how to treat research history as 'lineage engineering,' requiring precise citation of specific preprints (arXiv version pinning), distinguishing between conference and journal versions, and transparently addressing concurrent results. This ensures the bibliography is rigorous, consistent, and withstands expert review.

A comprehensive guide for authors submitting to top-tier Software Engineering (SE) conferences (like FSE, ICSE). It details how to structure the Related Work section by focusing on the 'delta'—the unique difference—between your work and prior art. It emphasizes covering the full SE literature landscape, maintaining anonymity, and correctly declaring overlaps with concurrent or prior versions.

A detailed guide on positioning a computer architecture paper within the broader academic literature. It teaches authors to write a 'lineage with structural deltas,' moving beyond mere citation lists. The guidelines cover sweeping multiple databases (like dblp and IEEE Xplore), identifying concrete structural improvements (deltas), and adhering to strict academic rules, such as citing all authors and maintaining un-blinded bibliography integrity.

A comprehensive guide for structuring the related work section in interdisciplinary HRI papers. It teaches authors how to simultaneously situate their research across multiple literatures—including robotics, HCI, psychology, and design—while employing a 'delta-first' argument to clearly articulate novelty and maintaining double-blind review compliance.

A comprehensive guide on how to structure the 'Related Work' section for top-tier theoretical computer science conferences (like ICALP). It teaches authors how to prove their results are genuinely new and better by precisely comparing their bounds against the best known literature, correctly crediting prior venues (STOC, FOCS, etc.), and maintaining academic rigor under double-blind guidelines.

A comprehensive guide for authors submitting to major signal processing conferences like ICASSP. It details how to audit, define, and precisely position a paper's novelty by comparing it against specific literature lanes (SPS journals, conferences, and ML venues). Learn to articulate the technical delta against the nearest work in a constrained, four-page format.

A comprehensive guide for structuring the "Related Work" section for top-tier computer vision conferences (ICCV, CVPR, ECCV). It covers best practices for citing intervening-cycle literature, managing concurrent preprints, ensuring double-blind anonymity, and correctly attributing source venues to maximize novelty perception and score highly with reviewers.

A comprehensive guide for positioning database research papers for top-tier conferences like ICDE. It teaches authors how to distinguish genuine novelty (new mechanisms) from engineering delta (implementation improvements), conduct deep literature audits, and compare their work against both academic venues and real-world production systems. Essential for improving manuscript eligibility and impact.

A comprehensive guide detailing how to structure the 'Related Work' section for submissions to top data mining conferences like ICDM. It emphasizes positioning the research based on core mechanisms and mining tasks, rather than simply listing results. The guide also provides critical advice on maintaining triple-blind anonymity, verifying citation venues (avoiding misattribution traps), and ensuring the novelty claim is distilled into a single, quotable mechanism-contrast sentence.