Skill UI

Provides strict guidelines for writing the Related Work section in theoretical database papers. It teaches authors how to precisely position their novel results against existing theorems (ICDT/PODS canon), covering complex topics like finite model theory, query complexity, and proper academic citation etiquette, ensuring genuine novelty is highlighted.

This guide provides a comprehensive framework for authors to position their work against existing literature, concurrent submissions, and public scrutiny in top-tier AI conferences. It teaches how to separate similar components from identical scientific problems, build verifiable novelty claims, and respond robustly to reviewer challenges.

This guide details the advanced methodology for structuring the 'Related Work' section for top-tier academic conferences (e.g., ASPLOS). It emphasizes positioning research across multiple parallel domains—including architecture, OS/systems, compilers, and accelerators—and defining the precise technical boundary where your work advances the state of the art.

This guide provides structured methodologies for authors to position their research within the context of existing literature and concurrent submissions at top-tier machine learning conferences (e.g., ICML, NeurIPS). It emphasizes identifying the technical delta, addressing novelty concerns, and properly citing related work to maximize acceptance chances.

A comprehensive guide for authors preparing the 'Related Work' section for top-tier robotics conferences like ICRA. It details how to conduct thorough literature reviews across multiple research 'lanes,' handle concurrent work (arXiv), properly self-cite under double-anonymous rules, and position the novelty against both academic rivals and commercial systems.

A detailed methodology guide for authors submitting to highly competitive software engineering venues (like ICSE). It teaches how to structure the Related Work section not as a bibliography, but as a 'delta statement' that explicitly outlines the unique differences and contributions compared to the state-of-the-art across multiple publication lanes (journals, preprints, flagship venues).

A comprehensive guide for auditing and positioning the novelty and eligibility of research submissions in the field of software maintenance and evolution. It teaches authors to write a 'delta-first' related work section, contrasting their contribution against key prior works and covering specialized literature lanes (e.g., MSR, ICSE, TSE) to demonstrate deep command of the academic community.

This comprehensive guide helps researchers position their work in Automatic Speech Recognition (ASR) and Spoken Language Understanding (SLU) for the IEEE ASRU workshop. It covers conference fit assessment, manuscript re-framing strategies, understanding venue-specific evidence requirements (e.g., decoding, robustness analysis), and differentiating the contribution from related fields like Interspeech or SLT. Use this tool for submission strategy and academic positioning.

A comprehensive guide for authors submitting to top-tier security conferences (e.g., IEEE S&P). It details best practices for constructing the 'Related Work' section, focusing on defining a clear 'security delta' statement, mapping coverage across multiple attack vectors, managing resubmission overlaps (40% rule), and verifying citation attribution using tools like dblp and IEEE Xplore.

Provides comprehensive guidelines for authors submitting to major AI conferences. It helps authors audit originality, properly cite prior art (including preprints, workshop papers, and rejected versions), manage dual-submission risks, and transform the related work section from a mere list into a compelling, novel argument that clearly positions the contribution.

This guide provides detailed instructions for authors on structuring the Related Work section for ACM IMC papers. It emphasizes that related work must cover not only prior claims but critically analyze prior datasets, vantage points, tools, and methodologies. It teaches techniques like delta-first positioning and proper venue attribution to demonstrate deep domain expertise and avoid common academic pitfalls.

This comprehensive guide teaches researchers how to sharply position their economic manuscripts. It helps identify the unique contribution (the 'delta') relative to the closest existing literature, especially when targeting high-impact journals like the IMF Economic Review (IMFER). It emphasizes connecting academic findings to global policy debates and differentiating the work from related fields (JIE, JIMF).