菜单
Summarize one saved reference by id or name from references/, reading TeX or Markdown files from original/ and writing summary/summary.md. Use when asked to summarize, understand, or make notes for a saved reference, paper, arXiv entry, or MinerU-parsed PDF.
| name | summarize-reference |
| description | Summarize one saved reference by id or name from references/, reading TeX or Markdown files from original/ and writing summary/summary.md. Use when asked to summarize, understand, or make notes for a saved reference, paper, arXiv entry, or MinerU-parsed PDF. |
Input is <id-or-name>. Locate references/<id-or-name>/original/.
.tex files in original/; otherwise use MinerU .md files.references/<id-or-name>/summary/summary.md; ensure summary/ and original/ are siblings.summary/summary.md before overwriting.Unknown when needed.# <Paper Title>
## Metadata
- **Source**: <path, URL, arXiv ID, or PDF filename>
- **Authors**: <authors or Unknown>
- **Year**: <year or Unknown>
## 一句话总结本文
## 1. 这篇论文试图解决什么问题？
## 2. 有哪些相关研究？
## 3. 论文如何解决这个问题？
## 4. 论文做了哪些实验？
## 5. 有什么可以进一步探索的点？
Write in the user's preferred language.
Report the summary path, whether it used TeX or Markdown, and any important uncertainty. Do not paste the full summary unless asked.
Add academic references from local PDFs or arXiv IDs into a references/ folder. Use when asked to add, download, parse, or organize PDFs/arXiv papers, using MinerU to convert PDFs and keeping only markdown plus images after parsing.
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.
Guides researchers through structured ideation frameworks to discover high-impact research directions. Use when exploring new problem spaces, pivoting between projects, or seeking novel angles on existing work.
Applies cognitive science frameworks for creative thinking to CS and AI research ideation. Use when seeking genuinely novel research directions by leveraging combinatorial creativity, analogical reasoning, constraint manipulation, and other empirically grounded creative strategies.
Write publication-ready ML/AI papers for NeurIPS, ICML, ICLR, ACL, AAAI, COLM. Use when drafting papers from research repos, structuring arguments, verifying citations, or preparing camera-ready submissions. For systems venues (OSDI, NSDI, ASPLOS, SOSP), use systems-paper-writing instead.
Generates conference presentation slides (Beamer LaTeX PDF and editable PPTX) from a compiled paper with speaker notes and talk script. Use when preparing oral talks, spotlight presentations, or invited talks for ML and systems conferences.