Skill UI

This guide provides a comprehensive pre-submission audit checklist for AAAI conference technical papers. It covers crucial aspects like double-blind anonymity, page limits, reproducibility requirements, author policies, and adherence to the latest AI-use guidelines. Use this before submitting to mitigate risks of desk rejection or policy violation.

A comprehensive guide for authors preparing rebuttals following AAMAS preliminary reviews. It details the specific constraints (e.g., double-blind, no new results), the strategies for addressing diverse technical reviewers (such as game theorists, MARL experts, and systems engineers), and the structured pattern required to maximize the impact of a short response window.

A comprehensive guide for authors transitioning an accepted, anonymous conference submission into the final, public camera-ready version for publication. It covers de-anonymization steps, including restoring author details, updating proceedings metadata, reflowing figures for multiagent papers, and integrating rebuttal promises without expanding the core contribution. This ensures adherence to strict publishing standards.

This guide helps authors audit the novelty and eligibility of multiagent system research for submission to AAMAS. It provides comprehensive advice on positioning the work against literature spanning multiple top-tier venues (e.g., NeurIPS, ICML, AAAI, EC, JAAMAS), integrating concepts from multiagent RL, game theory, and social choice. It ensures submissions are positioned accurately compared to the broader academic community, maximizing impact and minimizing rejection risk.

This comprehensive guide provides a detailed audit checklist for authors submitting to the AAMAS conference. It covers verifying the correct conference track, maintaining double-blind anonymity, adhering to strict formatting rules (e.g., page limits, supplementary zip caps), and identifying potential submission-blocking risks to ensure readiness before the deadline.

Provides comprehensive guidelines for authors preparing supplementary materials for conference submissions (AAMAS). It covers structuring full proofs, extended game definitions, extra experiments, and anonymized code assets, ensuring the main paper remains comprehensible while maximizing the impact of supporting evidence.

Provides comprehensive guidelines for authors submitting papers to Acta Automatica Sinica (AAS). It details how to organize and present anonymous, reproducible code, data, and experimental artifacts to enhance the credibility and rigor of research in control, automation, and pattern recognition, supporting the double-blind review process.

Provides a comprehensive guide for authors responding to peer reviewer feedback and revision comments for top-tier academic journals. It teaches structured rebuttal writing, handling disagreements while maintaining professionalism, and managing multi-round revisions to systematically increase publication probability.

This comprehensive guide provides authors with a detailed checklist for the post-acceptance, camera-ready phase for Acta Automatica Sinica (AAS). It walks users through all necessary steps, including restoring full author details, applying the specific journal template, meticulous proofreading of formulas, figures, and references (GB/T 7714), and understanding publication and royalty procedures. Use this to ensure your manuscript is zero-defect before publication.

A comprehensive guide for designing and presenting rigorous experiments and simulations for top-tier journals in Control Theory, Robotics, and Smart Systems. Covers RQ-driven design, establishing fair baselines, providing theoretical proofs of stability/convergence, performing ablation studies, and ensuring statistical significance, helping authors build an undeniable evidence chain for double-blind external review.

A comprehensive guide on writing literature reviews and related work sections, specifically tailored for high-impact journals like Acta Automatica Sinica (AAS). It teaches authors how to frame their research by focusing on the incremental contribution (delta), moving beyond simple literature listing to establish clear gaps, contrasting current limitations, and rigorously defining the work's novelty in a structured manner.

Provides comprehensive guidelines for achieving scientific reproducibility in academic research, particularly for control systems, automation, and pattern recognition. It covers fixing environment dependencies, data handling, random seeds, and process pipelines, helping authors withstand rigorous peer review questioning and build verifiable research artifacts.