Skill UI

This guide provides best practices for structuring complex academic manuscripts, particularly for conferences requiring a single-PDF submission model. It details how to optimally split content between the limited body (e.g., 12 pages) and the extensive appendix, ensuring that the crucial theorems, proofs, and auxiliary lemmas are presented in a verifiable and highly readable manner for peer reviewers. Key techniques include implementing restatement discipline and writing roadmap paragraphs for clear verification paths.

Provides a comprehensive guide for authors responding to highly technical conference reviews, particularly focusing on the critical 'one-shot major revision response letter.' It details strategies for maintaining strict double-anonymity, structuring the rebuttal around decision-critical points (soundness, reproducibility), and creating a detailed change ledger to systematically address every minimum necessary change requested by reviewers.

This comprehensive guide details the academic review pipeline for CoNEXT conference submissions. It covers double-anonymous double-blind review, the two-round TPC process, and the critical nature of the one-shot "major revision," which functions similarly to a journal's revise-and-resubmit cycle. It provides authors with strategic insights to structure their research for rigorous academic scrutiny.

This skill guides authors on how to position, structure, and strengthen empirical Natural Language Processing (NLP) manuscripts for submission to the Conference on Empirical Methods in Natural Language Processing (EMNLP). It provides deep insights into conference fit, required evidence (baselines, error analysis, datasets), proper framing, and anticipating reviewer expectations for top-tier AI venues.

This guide helps authors position their machine learning systems manuscripts for the rigorous Conference on Machine Learning and Systems (MLSys). It details the venue's specific focus on system-level contributions, including training/inference infrastructure, compilers, data systems, and hardware-aware ML. Learn how to frame your work to appeal to systems reviewers by emphasizing measurable impacts on capability, cost, reliability, or deployment scale.

A comprehensive guide for authors preparing a single-page academic rebuttal for top-tier AI conferences (e.g., CoRL). It details how to structure the response, focusing on maximizing impact through new, compact evidence (tables/figures) rather than verbose prose. Learn to triage reviewer comments, maintain a professional tone for public record, and optimize space for maximum score movement.

This tool models the comprehensive, multi-stage academic review pipeline used by CoRL (Conference on Robot Learning). It simulates the entire double-anonymous review process, including reviewer assignment, initial first-round rejection gates, the critical author rebuttal window, and the multi-tiered decision-making hierarchy (Reviewers -> ACs -> SACs). It helps authors understand where their efforts have the highest leverage in influencing the paper's outcome.

A comprehensive guide detailing the submission rules and best practices for supplementary materials, including videos, appendices, code, and data, for top-tier robotics conferences. It outlines distinct submission channels, strict technical requirements (e.g., 250MB video cap, anonymity), and the necessary transition steps from the review phase to the final camera-ready publication format.

This skill provides a comprehensive, year-round workflow guide for submitting research papers to the CoRL Conference on Robot Learning. It meticulously breaks down the annual cycle into manageable phases—including pre-submission preparation, managing reviewer feedback, crafting rebuttals, and preparing camera-ready versions. It assists teams in planning their efforts across critical milestones and navigating the academic publishing process.

A specialized routing tool designed for academic researchers submitting manuscripts to top-tier Computer Science and AI conferences. It helps users navigate complex decision points, such as selecting the best venue (e.g., ICML vs NeurIPS), matching contribution types (theory, system, empirical study), and adhering to specific submission guidelines and review constraints.

This guide details the rigorous academic review process, modeled after top-tier conferences like CSCW. It breaks down the decision vocabulary (e.g., Revise and Resubmit, Conditional Accept, Reject), explaining what each outcome means for authors. It also covers the critical mechanics of same-reviewer re-review, the shift to a rolling editorial board structure, and practical advice on interpreting waiting times and revising submissions.

A comprehensive guide for drafting a single-page academic rebuttal after conference reviews (e.g., CVPR). It teaches authors how to strategically address multiple reviews, correct factual errors, and clarify scope within strict formatting and content limitations, focusing on the Area Chair's perspective and emphasizing data over adjectives.