Skill UI

This guide models the entire lifecycle of academic conference submissions, detailing stages like bidding, review writing, author response, and decision-making. It helps researchers strategically plan their work to maximize impact, preemptively address potential weaknesses, and optimize their research communication strategy in a competitive academic environment.

A comprehensive guide for authors submitting to venues focused on probabilistic AI, including UAI. It emphasizes achieving maximum formal rigor by enforcing strict notational discipline, clearly separating conditioning from intervention, explicitly stating assumptions, structuring the main body for maximum impact, and calibrating claims to match empirical evidence. Essential for papers involving graphical models, causality, and Bayesian methods.

A specialized guide for assessing whether a storage systems or file system manuscript fits the USENIX FAST conference. It covers venue positioning, required evidence (realistic workloads, fault models), appropriate framing, and comparison methodologies necessary for top-tier systems conference submissions.

A comprehensive audit checklist for designing and evaluating security experiments, adhering to the highest academic standards (e.g., USENIX Security). It guides users through verifying adaptive attacker models, calculating precision at realistic base rates, ensuring statistical honesty for stochastic results, and maintaining ethical compliance when working with live systems.

This guide models the comprehensive two-round, journal-style peer review process used at major computer vision conferences like WACV. It details the distinct stages: Round 1 outcomes (Accept, Revise and Resubmit, Reject), the optional R1 rebuttal phase, and the final R2 decision. It emphasizes that the most critical phase for authors is executing high-quality revisions during the Revise-and-Resubmit stage, rather than solely relying on rebuttals.

A comprehensive guide detailing when and how to structure theoretical models in development economics research, particularly for World Bank Economic Review submissions. It emphasizes that models must serve a functional purpose—such as interpreting empirical coefficients, running policy counterfactuals, or aggregating to welfare statements—rather than being decorative. Key principles cover parameter identification, matching structural frictions to the local setting, and handling counterfactual assumptions (Lucas critique).

Provides comprehensive guidelines for packaging and submitting research artifacts (datasets, models, code) for major conferences. It details the difference between mere 'existence' (badge verification) and true academic 'reproducibility,' covering archival strategies, web data licensing, takedown resilience, and minimal viable package structure for long-term scholarly impact.

This skill models the entire peer-review pipeline for Web Conferences (WWW), detailing the stages from abstract submission to final notification. It guides authors and reviewers on the implications of track-scoped double-blind review, emphasizing criteria such as Web-centricity, evidence scale, and ethical considerations required for acceptance.

This comprehensive guide outlines best practices for packaging research artifacts, including code, proprietary data logs, and models, for submission to top-tier academic venues. It addresses the crucial need for verifiability and reproducibility, providing strategies for handling limited space, proprietary datasets, and the absence of formal artifact grading systems, ensuring high academic credibility.

This guide teaches researchers how to strategically position a paper's contribution within established academic lineages (e.g., click models, LTR). It emphasizes moving beyond simple citation coverage to writing precise 'contrast sentences' that articulate the technical delta, ensuring the work's novelty is clearly defined relative to neighboring venues like SIGIR and KDD. Ideal for authors refining their technical writing for top-tier conferences.

Helps marketers choose and interpret attribution models, reconcile conflicting conversion numbers across platforms, and build first-party attribution to identify channels that truly drive revenue.

This guide provides a structured framework for presenting complex empirical results in academic manuscripts, particularly for international marketing journals. It details the essential 'spine exhibits' (conceptual models, invariance tables, cross-national patterns) and teaches techniques like the 'claim test' and 'triage' to ensure arguments are clear, rigorous, and adhere to strict page limits.