Skill UI

A comprehensive guide for drafting the Related Work section for top-tier networking conferences (e.g., CoNEXT, SIGCOMM). It emphasizes moving beyond simple literature summaries to create a 'delta argument'—clearly defining what the paper contributes over the closest prior work. Guidelines cover covering specific networking 'lanes' (like IMC, NSDI, SIGMETRICS), maintaining double-anonymous citations, and ensuring the contribution is concrete and testable.

This guide teaches how to precisely position a new research result within the formal theoretical lineage of existing literature. Unlike a general literature review, this method focuses on defining the formal relationship (e.g., nesting, generalization, assumption weakening) between your contribution and the closest prior work, minimizing credibility risks in academic publishing.

This guide details the necessary steps for achieving and reporting reproducibility in Human-Robot Interaction (HRI) studies. Since HRI involves unique elements like human participants and physical environments, reproducibility focuses on making the study protocol, robot behavior specifications, analysis code, and de-identified data transparent. Learn how to properly assemble a comprehensive replication package and ethically disclose limitations to enhance academic credibility in top-tier HRI publications.

A comprehensive guide for academic researchers detailing how to achieve and disclose full reproducibility for Computer Vision and deep learning models. Covers essential practices such as protocol pinning for foundation models, detailed logging of datasets, hardware specifications, and variance honesty, ensuring results remain verifiable years after publication.

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).

This guide provides a comprehensive framework for authors targeting elite AI/ML conferences like ICML. It covers academic positioning, identifying core ML contributions, structuring the narrative (Problem, Why Now, What is New), and establishing a rigorous evidence bar, including baselines and ablations. It also advises on distinguishing the work from closely related venues (e.g., NeurIPS, ICLR).

This skill guides authors in transforming raw experimental data into a compelling, logically structured scientific narrative suitable for top-tier journals like JACS. It teaches how to explicitly define the 'chemical advance' by building an evidence-backed claim chain: Problem $ ightarrow$ Advance $ ightarrow$ Evidence $ ightarrow$ Significance. It ensures that every claim of novelty is rigorously supported by data and compares the work explicitly against the closest prior art.

A guide for authors on strategically positioning their academic manuscript within specialized fields, particularly accounting and finance. It teaches how to move beyond simply identifying a 'gap' to joining a specific academic 'conversation.' The guide emphasizes stating the marginal contribution relative to the closest prior work and justifying the submission venue (e.g., JAR vs. JAE).

A comprehensive guide for authors on how to structure the literature review and introduction of academic papers, especially in banking and finance. It teaches how to precisely identify and articulate a unique contribution ('delta') relative to the closest existing literature, ensuring the paper is seen as a specialized advancement rather than a generic survey.

A comprehensive guide for academic authors on how to precisely position their research within the specialized field of corporate finance. It teaches how to identify the specific theoretical 'strand' (e.g., capital structure, governance, M&A) and articulate a clear, marginal contribution by contrasting the work against 2-3 closest existing papers, thereby transforming vague claims into rigorous academic arguments.

This guide teaches systematic methods for positioning a research manuscript's marginal contribution, particularly for general-interest academic journals. It emphasizes locating the true academic frontier, explicitly naming 2-3 closest preceding works, and articulating the novel 'delta' in one sentence. The goal is to pass the 'travel test'—demonstrating why the finding matters to a broad, non-specialist readership.

This guide helps writers structure academic syntheses to maintain rigorous objectivity, ensuring that the work summarizes the full spectrum of competing views rather than advocating for a single position. It details how to properly 'steelman' opposing arguments, weigh evidence impartially, separate positive findings from normative policy judgment, and honestly disclose areas of uncertainty.