Skill UI

This comprehensive guide walks authors through the critical final stages after conference acceptance. It covers de-anonymization, ensuring proper metadata for proceedings volumes (PMLR), integrating all reviewer responses, regenerating figures, and preparing for physical/virtual presentations (posters and spotlights). Use this to manage the entire complex workflow from acceptance to final submission.

A comprehensive guide for authors submitting to UAI (Uncertainty in Artificial Intelligence). It details how to position research by ensuring coverage across diverse academic communities, including Machine Learning, Statistics, Causal Inference, and foundational mathematics. Focuses on establishing the technical 'delta' rather than merely listing citations, helping authors avoid common review failures.

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.

This comprehensive pre-upload audit guide ensures submissions meet the strict technical and anonymity requirements for UAI OpenReview. It covers critical aspects like the 8-page main body constraint, combining all content into a single PDF, handling file size caps (15MB/50MB), and performing an identity sweep to maintain double-blind review standards.

This guide details the strategic placement of content for academic submissions, dividing material into Main Part, Appendix, and Supplementary ZIP. It provides best practices for authors to manage proofs, protocols, and code while adhering to strict page limits and double-blind review constraints, ensuring maximum review integrity and clarity.

A comprehensive project management layer designed for navigating the entire academic conference lifecycle. It guides authors through critical phases, including topic selection, paper drafting, rigorous review response, camera-ready submission, and final presentation. The workflow emphasizes meticulous planning, role assignment, and maintaining academic integrity to prevent common project failures.

A comprehensive guide detailing how to package and present research artifacts—including code, hardware designs, and datasets—for major academic conferences. It outlines best practices for both initial review-time evidence and long-term public reuse, ensuring reproducibility and maximizing the chances of adoption by future builders.

A comprehensive guide to navigating the UIST (User Interface Software and Technology) academic review pipeline. It details every stage, from initial submission and expert review to the rebuttal phase and final committee decisions. The guide teaches authors how to critically analyze reviewer feedback, identify evidence gaps, strengthen novelty claims, and strategically plan for conditional acceptance or resubmission.

A comprehensive guide for producing the mandatory supplementary video figure for UIST submissions. This material treats the 3-minute video as core evidence, detailing requirements for resolution (1080p/4K), codec (H.264), and anonymity. It guides authors on scripting the video around key claims, ensuring uncut interaction loops, and maintaining academic rigor to convince reviewers of the system's reality.

A specialized guide for authors aiming to submit to the Conference on Uncertainty in Artificial Intelligence (UAI). It provides expert advice on framing the core contribution—such as probabilistic reasoning, causal inference, and uncertainty modeling—and calibrating the manuscript for highly technical, statistical ML reviewers. Use this skill to refine your submission strategy, identify evidence gaps, and properly position your work relative to other top-tier AI venues like AISTATS and IJCAI.

A comprehensive guide for positioning computer science manuscripts for top-tier security conferences like USENIX Security. It covers core topics (systems, network, privacy, software security), required evidence (rigorous artifact, measurement, vulnerability analysis), and strategic advice on framing the work to meet adversarial reviewer expectations. Ideal for authors preparing high-stakes academic submissions.

A comprehensive guide detailing the mandatory and optional evaluation phases for academic security artifacts, such as those required for USENIX Security. It covers Phase-1 (availability) checks and Phase-2 (functionality, reproducibility) requirements. Provides best practices for structuring code, managing technical hazards (e.g., dangerous-by-default behavior), and ensuring verifiable, reproducible results for peer review.