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runtsang
GitHub 创作者资料

runtsang

按仓库查看 1 个 GitHub 仓库中的 21 个已收集 skills。

已收集 skills
21
仓库
1
更新
2026年4月1日
仓库分布

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skills
其他高等院校教师

Multi-stage rebuttal analysis skill for RebuttalStudio. Use when organizing reviewer comments into stage-specific conference workflows, including stage1 breakdown, stage2 refinement, stage4 multi-round follow-up, and stage5 final remarks generation.

2026年4月1日
text-condense
技术写作员

Condense rebuttal prose into fewer words without changing the original meaning. Use when a response block, paragraph, or selected passage is too long but all technical content, citations, and commitments must stay intact. Supports academic English.

2026年4月1日
document-memory-summarize
其他高等院校教师

Summarize extracted paper text into concise Markdown memory for later Stage 2 and Stage 4 background use, with fixed section headings and no fabricated claims.

2026年3月27日
stage1-neurips-breakdown
编辑

Break down full NeurIPS reviewer responses into structured rebuttal units. Use when input contains NeurIPS reviewer fields (Summary, Strengths and Weaknesses, Questions, Limitations) and numeric scores (Rating, Confidence, Quality, Clarity, Significance,…

2026年3月3日
stage2-neurips-refine
编辑

Refine a Stage2 NeurIPS 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.

2026年3月3日
stage1-arr-breakdown
编辑

Break down full ARR (ACL Rolling Review) reviewer responses into structured rebuttal units. Use when input contains ARR reviewer fields (Paper Summary, Strengths, Weaknesses, Comments/Suggestions) and numeric scores (Confidence, Soundness, Excitement, Overall…

2026年3月3日
stage2-arr-refine
编辑

Refine a Stage2 ARR (ACL Rolling Review) 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.

2026年3月3日
stage1-iclr-breakdown
编辑

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…

2026年3月1日
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