Skill UI

This guide provides best practices for authors writing the Related Work section for top-tier AI conferences (e.g., ECAI). It instructs users on how to cover diverse AI lanes (symbolic, learning, multi-agent, application) for broad reviewers, employ 'Delta-first' positioning to state novelty concisely, and adhere to strict page budgets and double-blind review rules.

This guide details the principles of conducting rigorous Monte Carlo simulations for econometric theory papers. It instructs users on designing simulations that test finite-sample behavior, ensuring that asymptotic approximations are useful and accurate across boundary cases (e.g., weak identification, heavy tails). Emphasis is placed on reproducibility, comprehensive metrics (bias, coverage, power), and ensuring the simulation supports the core theory.

A comprehensive guide for building a 'robustness battery' to validate empirical findings. It instructs researchers on thoroughly testing results against potential weaknesses in specification, sample selection, measurement, estimator choice, and inference assumptions. Essential for publishing rigorous, credible quantitative research.

A deep dive into the best practices for drafting the Related Work section for top-tier NLP conferences (like EMNLP). This guide instructs authors on how to trace task lineage, verify dataset ancestry, manage concurrent work citations (arXiv vs. Anthology), and ensure rigorous citation hygiene to withstand expert reviewer scrutiny.

A comprehensive guide for researchers submitting NLP papers, detailing best practices for achieving high reproducibility. It instructs users to pin model versions, log data provenance, report compute costs, and adhere rigorously to the Responsible NLP checklist. Essential for ensuring academic integrity and enabling rigorous verification of ML experiments.

This comprehensive guide details the structure and scientific rigor required for writing a high-impact cover letter and editor pitch for academic journals, such as EPSL. It instructs authors to shift focus from merely describing data to quantifying the 'frontier advance,' demonstrating result portability, and strategically suggesting cross-disciplinary reviewers to maximize the manuscript's chances of acceptance.

This guide instructs authors on how to craft a robust, cross-disciplinary gap statement for high-level earth science journals. It teaches that a paper's contribution must be framed by triangulating evidence across multiple sub-fields (geochemistry, geophysics, geodynamics, etc.) and competing hypotheses, rather than focusing solely on a single methodological community.

A comprehensive guide for environmental science manuscripts, detailing the standards required for data reporting and ensuring research reproducibility. It instructs authors on assembling Supporting Information (SI), writing data-availability statements, and depositing raw data, code, and protocols into recognized public repositories (e.g., Zenodo, GenBank).

This guide provides a rigorous methodology for articulating the unique dual contribution of a paper in Entrepreneurship Theory and Practice (ETP). It teaches authors how to match specific theoretical claims (e.g., new constructs, boundary conditions) with actionable, mechanism-derived practice implications, ensuring the contribution is earned by the evidence.

A comprehensive guide for revising academic papers submitted to FAccT (Fairness, Accountability, and Transparency). It instructs authors on how to frame socio-technical contributions to be legible to a mixed panel of computer scientists, lawyers, and social scientists. Focus areas include scoping claims to specific populations, explicitly arguing adverse impacts, and making interdisciplinary concepts native to the text.

This guide instructs authors on crafting highly targeted and convincing robustness sections for empirical finance papers. Instead of merely adding volume, it teaches the concept of 'subtraction, then precision'—identifying specific alternative explanations (threats) a referee might raise (e.g., reverse causality, omitted variables) and selecting the minimal, most effective check to neutralize each threat. This aligns with the philosophy of top-tier financial journals that value new ideas over superficial testing.

This comprehensive skill guides users to assess whether a forest science manuscript is suitable for the 'Forest Ecology and Management' journal. It instructs reviewers to check for sound ecological evidence paired with explicit management or restoration relevance. The assessment covers topics like silviculture, disturbance, and stand dynamics, ensuring the study provides actionable insights for conservation and management, rather than just pattern description.