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Turn a research report and experiment results into an English paper with figures, LaTeX source, and a compiled PDF. Coordinate planning, drafting, Gemini reviews, and two revision rounds, preserving PDFs and an improvement log.
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Turn research code and experimental results into ML and AI paper drafts. The skill guides argument structure, reference verification, and conference formatting with LaTeX templates, helping researchers revise drafts and prepare submissions.
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Turn research code and experimental results into ML and AI paper drafts. Clarify the main contribution, connect claims to evidence, find and verify references, and prepare conference submissions using LaTeX templates and review checklists.
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Prepare machine learning and AI research papers, from literature searches and experiment planning to analysis, drafting, and submission preparation. The workflow connects experiments to research claims and includes citation verification and revisions in response to reviews.
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Draft a research paper section by section in LaTeX, a document typesetting format, using an outline and research materials. Apply venue formatting, incorporate figures, verify bibliography records, and check that repeated theoretical statements agree.
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Turn a research paper into a conference poster using HTML/CSS and figures from the paper. Check claims against evidence, measure the print layout, and produce a PDF matched to the venue’s required dimensions.
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Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, conducting literature reviews, finding related work, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, citation verification workflows, and paper discovery/evaluation criteria.
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Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, conducting literature reviews, finding related work, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, citation verification workflows, and paper discovery/evaluation criteria.
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Write publication-ready ML/AI/Systems papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM, OSDI, NSDI, ASPLOS, SOSP. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification workflows.
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Write publication-ready ML/AI/Systems papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM, OSDI, NSDI, ASPLOS, SOSP. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. Includes LaTeX templates, reviewer guidelines, and citation verification workflows.
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Three modes for CS-conference papers (CVPR/ICCV/ECCV vision, ACL/EMNLP/NAACL NLP, ICLR/NeurIPS/ICML/AAAI ML). DIRECT-EDIT mode (common): the user describes a change in Chinese or English and the manuscript (LaTeX or Markdown) is edited directly through a CS-venue writing toolkit with author sign-off (use for 改这段 / 把中文想法写成 latex / polish / de-AI / translate / compress a passage). REVIEW mode (occasional, pre-submission): harden the paper through an adversarial courtroom review engine (N holistic domain reviewers / contestability routing / two-sided trial / three-way verdict / clerk-converged multi-round loop) with consensus-gated, author-signed revisions (use for review / critique / 审稿 / 评审 / mock-review). AUTO mode (unattended, opt-in via /goal): run the review-revise loop toward a verifiable goal, applying safe fixes under a drift-bounded policy and queueing risky ones. Resolves all inputs at runtime, no hardcoded paths. Not a from-scratch drafter (use ml-paper-writing) and not an official-venue rebuttal.
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Refine a Stage2 ICLR rebuttal draft into polished, reviewer-facing prose in the author's style; preserve factual grounding, optionally prepend a courteous opening phrase, and normalize tables/code/formulas into Markdown.
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Break down full ICLR reviewer responses into structured rebuttal units. Use when input contains reviewer summary/presentation/contribution/strength/weakness/question text and the goal is to split weaknesses/questions into granular R-style response items while preserving original wording for quoted issues.
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Escreva papers prontos para publicação em NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use quando estiver elaborando papers a partir de repositórios de pesquisa, estruturando argumentos, verificando citações ou preparando submissões finais. Inclui templates LaTeX, diretrizes de revisores e workflows de verificação de citações.
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Write ML papers for NeurIPS/ICML/ICLR: design→submit.
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Build a section-by-section paper outline from experiment results and review findings. Map claims to evidence, allocate pages for the target venue, and plan figures and citations in PAPER_PLAN.md before drafting the paper.
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Turn a paper outline and research narrative into a section-by-section LaTeX draft. Incorporate figures and verified bibliography entries, adapt formatting to the target venue, and review clarity, evidence alignment, and consistency across sections.
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Turn a research paper into a conference poster using its figures and findings. Produce one HTML/CSS file and a print-ready PDF, with measured layout checks and Gemini reviews of content accuracy and final appearance.
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Build a paper outline from experiment results and review conclusions. Map claims to evidence, plan sections, figures, and citations, and allocate pages for the target venue, with another model reviewing the outline before it is finalized.
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Prepare a conference talk from a completed paper, including an outline, Beamer slides, editable PPTX, speaker notes, and a full script. Polish the visuals, check exported files, and optionally audit claims, citations, and anonymity.
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Use Gemini to discover research papers through related problems and alternative terminology. Results are organized into a table with publication details, code links, and short summaries, with filters for year, venue, and available code.
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Creates figures for machine learning papers from draft text or experiment data. Extracts components for Gemini-generated diagrams, chooses suitable charts with matplotlib or seaborn, and adjusts colors, fonts, and export formats for publication.
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Generates publication-quality figures for ML papers from research context. Given a paper section or description, extracts system components and relationships to generate architecture diagrams via Gemini. Given experiment results or data, auto-selects chart type and generates data-driven figures via matplotlib/seaborn. Use when creating any figure for a conference paper.
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Generate prompts for AI image tools to produce modern ML/RL paper-style figures matching the aesthetic of recent ICLR/NeurIPS/ICML 2024-2025 publications. Key traits — pure white canvas, white panels with soft drop shadow, rounded friendly font (Nunito/Poppins), densely packed but uncluttered floating elements, small pastel token squares, rich inline illustrations, colored keyword text, pill-shaped concept labels. Trigger phrases — "pastel风格论文配图", "现代ML论文配图", "modern ML figure prompt".
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