Skill UI

This comprehensive guide provides expert advice on structuring and polishing research manuscripts for multi-disciplinary academic venues like CIKM. It details how to satisfy reviewers from Information Retrieval, Data Mining, and Knowledge Management simultaneously, covering the optimal structure for the opening page, vocabulary discipline, budget compression, and effective title optimization.

A comprehensive guide for authors submitting academic papers, detailing how to proactively provide reproducible code, datasets, and experimental scripts. This ensures that research results are verifiable and trustworthy, significantly enhancing the credibility of findings in high-tier journals despite the absence of formal artifact evaluation badges.

This comprehensive guide details the critical steps authors must follow after their manuscript is accepted for publication in a major academic journal (e.g., CJC). It covers everything from signing copyright agreements and confirming author details to meticulous final layout checks, proper citation formatting (GB/T 7714), and strict rules for the proofreading stage. The focus is on ensuring the paper is delivered to print with zero errors, emphasizing that the stage is for correction, not substantive revision.

A comprehensive guide on structuring and writing the 'Related Work' and literature review sections for high-impact, comprehensive computer science journals. It emphasizes establishing the research gap (the 'delta'), structuring comparisons (Classification-Comparison-Gap), balancing literature coverage (classic vs. modern, local vs. global), and adhering to academic citation norms (e.g., GB/T 7714). Essential for authors needing to clearly define their novelty in a cross-disciplinary context.

A comprehensive pre-submission audit checklist tailored for submitting high-level, long-form academic papers to prestigious Chinese journals, such as the Chinese Journal of Computers (CJC). It guides authors through critical checks covering formatting standards, ethical guidelines (plagiarism and self-plagiarism), required components (abstracts, keywords, citations), and the optimal submission workflow, ensuring the manuscript meets the stringent requirements of top-tier academic publications.

This guide provides detailed rules for structuring long-form academic papers submitted to the Chinese Journal of Computers (CJC). It teaches authors how to strategically divide content into the main text, appendices, and supplementary materials. The core principle emphasizes that all decision-making evidence required for acceptance must reside in the main manuscript, while supporting details, full proofs, and extra tables belong in supplementary sections.

This skill systematizes the entire academic publishing journey for long-form papers, specifically targeting the requirements of top-tier journals like the Chinese Journal of Computers (CJC). It maps out the complete timeline from initial topic selection, through experimentation, writing, submission, multi-stage peer review, revision, and final publication, providing critical checkpoints and best practices to ensure a systematic and successful process.

This comprehensive guide provides authors with detailed standards for preparing high-quality, publishable scientific manuscripts for the Chinese Journal of Computers (CJC). It covers critical academic elements, including writing the four-element reporting abstract, structuring the narrative (Introduction, Methods, Experiments), maintaining consistent terminology and symbols, adhering to Chinese legislative units, and mastering the GB/T 7714 citation format. It ensures the final submission meets the rigorous linguistic and structural demands of top-tier academic journals.

A comprehensive guide for structuring the algorithm section of academic papers. It details the crucial steps for deciding on the solution route—whether to use commercial solvers, exact algorithms, or meta-heuristics. It emphasizes the requirement for rigorous pseudo-code, property analysis, and multi-level baseline comparisons to prove algorithmic novelty and contribution.

A comprehensive guide detailing the meticulous steps required to transform an accepted conference paper into its final, public, camera-ready version. It covers de-anonymization, integrating complex reviewer feedback, coordinating artifact release, and ensuring consistency with the permanently recorded OpenReview forum.

This comprehensive guide provides expert protocols for writing the 'Related Work' section in Machine Learning papers. It teaches authors how to maintain 'versioned honesty' by meticulously triaging the literature into distinct lanes (e.g., method lineage, model artifacts, evaluation infrastructure). It covers advanced topics like managing concurrent work, citing arXiv status accurately, and avoiding self-citation violations, ensuring the paper is positioned rigorously within the rapidly evolving academic field.

A comprehensive guide detailing best practices for ensuring the reproducibility of computational claims in Large Language Model (LLM) papers. It outlines a layered approach (Exact, Budgeted, Drifting) for verifying results, providing protocols for handling open-weight checkpoints, proprietary API models, and documenting compute costs and failure modes honestly.