菜单
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.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
Merge multiple fine-tuned models using mergekit to combine capabilities without retraining. Use when creating specialized models by blending domain-specific expertise (math + coding + chat), improving performance beyond single models, or experimenting rapidly with model variants. Covers SLERP, TIES-Merging, DARE, Task Arithmetic, linear merging, and production deployment strategies.
Compiles any research input — PDF papers, GitHub repositories, experiment logs, code directories, or raw notes — into a complete Agent-Native Research Artifact (ARA) with cognitive layer (claims, concepts, heuristics), physical layer (configs, code stubs), exploration graph, and grounded evidence. Use when ingesting a paper or codebase into a structured, machine-executable knowledge package, building an ARA from scratch, or converting research outputs into a falsifiable, agent-traversable form.
Records research provenance as a post-task epilogue, scanning conversation history at the end of a coding or research session to extract decisions, experiments, dead ends, claims, heuristics, and pivots, and writing them into the ara/ directory with user-vs-AI provenance tags. Use as a session epilogue — never during execution — to maintain a faithful, auditable trace of how a research project actually evolved.
Performs ARA Seal Level 2 semantic epistemic review on Agent-Native Research Artifacts, scoring six dimensions (evidence relevance, falsifiability, scope calibration, argument coherence, exploration integrity, methodological rigor) and producing a constructive, severity-ranked report with a Strong Accept-to-Reject recommendation. Use after Level 1 structural validation passes, when an ARA needs an objective epistemic critique before publication or release.
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.
Comprehensive guide for writing systems papers targeting OSDI, SOSP, ASPLOS, NSDI, and EuroSys. Provides paragraph-level structural blueprints, writing patterns, venue-specific checklists, reviewer guidelines, LaTeX templates, and conference deadlines. Use this skill for all systems conference paper writing.
| name | presenting-conference-talks |
| description | 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. |
| version | 1.0.0 |
| author | Orchestra Research |
| license | MIT |
| tags | ["Presenting Conference Talks","Beamer","PPTX","Slides","Speaker Notes","OSDI","SOSP","ASPLOS","NeurIPS","ICML"] |
| dependencies | ["python-pptx>=0.6.21"] |
Generate conference presentation slides from a compiled research paper. Produces both Beamer LaTeX PDF (for polished typesetting) and editable PPTX (for last-minute adjustments), with speaker notes and an optional talk script.
| Scenario | Use This Skill | Use Other Skills Instead |
|---|---|---|
| Preparing oral/spotlight/poster-talk slides | ✅ | |
| Generating Beamer PDF + PPTX from paper | ✅ | |
| Speaker notes and talk script | ✅ | |
| Writing the paper itself | ml-paper-writing | |
| Structuring a systems paper | systems-paper-writing | |
| Creating publication-quality plots | academic-plotting |
Attribution: This skill's structure draws inspiration from the ARIS paper-slides skill (570 lines, supporting poster/spotlight/oral/invited with Beamer+PPTX). This is an independent implementation for the AI-Research-SKILLs ecosystem.
| Talk Type | Duration | Slides | Content Depth |
|---|---|---|---|
| poster-talk | 3–5 min | 5–8 | Problem + key result only |
| spotlight | 5–8 min | 8–12 | Problem + approach + key results |
| oral | 15–20 min | 15–22 | Full story with evaluation highlights |
| invited | 30–45 min | 25–40 | Deep dive with context and demos |
Rule of thumb: ~1 slide per minute for oral, ~1.5 slides per minute for spotlight.
Slide 1: Title + Authors + Affiliation
Slide 2: Problem — Why this matters (1 motivating figure)
Slide 3: Key Insight — One-sentence thesis
Slide 4: Approach Overview — Architecture diagram
Slide 5: Main Result — Headline numbers (1 figure)
Slide 6: Takeaway + QR code to paper/code
Slide 1: Title + Authors
Slide 2: Problem Statement — Concrete, quantified
Slide 3: Motivation — Why existing solutions fall short
Slide 4: Key Insight — Thesis statement
Slide 5: System Overview — Architecture diagram
Slide 6: Design Highlight 1 — Core mechanism
Slide 7: Design Highlight 2 — Key innovation
Slide 8: Evaluation Setup — Baselines and workloads (brief)
Slide 9: Main Results — Headline performance figure
Slide 10: Ablation / Breakdown — What contributes most
Slide 11: Summary + Contributions
Slide 12: Thank You + Links
Slide 1: Title + Authors + Venue
Slide 2: Outline (optional — "roadmap" slide)
Slide 3: Problem Context — Domain importance
Slide 4: Problem Statement — Specific challenge
Slide 5: Motivation — Gaps in existing systems
Slide 6: Key Insight — Thesis
Slide 7: System Overview — Architecture diagram
Slide 8: Design Component 1 — Detailed walkthrough
Slide 9: Design Component 2 — Detailed walkthrough
Slide 10: Design Component 3 — Detailed walkthrough
Slide 11: Design Alternatives — Why not other approaches
Slide 12: Implementation — Key engineering highlights
Slide 13: Evaluation Setup — Testbed, baselines, metrics
Slide 14: End-to-End Results — Main performance
Slide 15: Result Deep Dive — Breakdown or per-workload
Slide 16: Ablation Study — Component contributions
Slide 17: Scalability — Scaling behavior
Slide 18: Demo Slide (systems talks) — Screenshot or recording
Slide 19: Related Work — Positioning (brief)
Slide 20: Summary — Contributions restated
Slide 21: Future Work — Open questions
Slide 22: Thank You + Paper Link + QR Code
Extends the oral structure with:
Systems conference talks have unique requirements compared to ML talks:
\only<N> or \onslide<N> for progressive reveal[Timing: X minutes]
[Key point to convey]
[Transition sentence to next slide]
Apply "Say what you're going to say, say it, then say what you said" at three levels:
Advantages: Professional typesetting, math support, version control friendly.
\documentclass[aspectratio=169]{beamer}
\usetheme{metropolis} % Clean, modern theme
\usepackage{appendixnumberbeamer}
\title{Your Paper Title}
\subtitle{Venue Year}
\author{Author 1 \and Author 2}
\institute{Institution}
\date{}
\begin{document}
\maketitle
\begin{frame}{Problem}
\begin{itemize}
\item Key problem statement
\item Concrete motivation with numbers
\end{itemize}
\note{Speaker note: Start with the big picture...}
\end{frame}
% ... more frames ...
\end{document}
Advantages: Easy last-minute edits, corporate template compatibility, animations.
from pptx import Presentation
from pptx.util import Inches, Pt
from pptx.enum.text import PP_ALIGN
prs = Presentation()
prs.slide_width = Inches(13.333) # 16:9
prs.slide_height = Inches(7.5)
# Title slide
slide = prs.slides.add_slide(prs.slide_layouts[0])
slide.shapes.title.text = "Your Paper Title"
slide.placeholders[1].text = "Author 1, Author 2\nVenue Year"
# Content slide
slide = prs.slides.add_slide(prs.slide_layouts[1])
slide.shapes.title.text = "Problem Statement"
body = slide.placeholders[1]
body.text = "Key point 1\nKey point 2"
# Add speaker notes
notes_slide = slide.notes_slide
notes_slide.notes_text_frame.text = "Speaker note: explain the motivation..."
prs.save("talk.pptx")
These are aesthetic suggestions, not official venue requirements. Adjust freely.
| Venue Type | Primary | Accent | Background |
|---|---|---|---|
| USENIX (OSDI/NSDI) | Dark Blue (#003366) | Red (#CC0000) | White |
| ACM (SOSP/ASPLOS) | ACM Blue (#0071BC) | Dark Gray (#333333) | White |
| NeurIPS | Purple (#7B2D8E) | Gold (#F0AD00) | White |
| ICML | Teal (#008080) | Orange (#FF6600) | White |
| Generic | Dark Gray (#333333) | Blue (#0066CC) | White |
- Read the compiled paper (PDF or LaTeX source)
- Identify: thesis, contributions, architecture figure, key eval figures
- Note the talk type and duration
- Select the appropriate slide structure template (above)
- Map paper sections to slide groups
- Allocate time per slide group
- Generate Beamer source slide by slide
- Add speaker notes per slide
- Include figures from paper (copy to slides/ directory)
- Generate python-pptx script for PPTX version
- Check total slide count matches talk duration
- Verify all figures are readable at presentation resolution
- Run Beamer compilation: latexmk -pdf slides.tex
- Run PPTX generation: python3 generate_slides.py
- Review speaker notes for timing and transitions
| Issue | Solution |
|---|---|
| Too many slides for time limit | Cut details, keep one figure per point |
| Slides feel like paper paragraphs | Use bullet points (≤ 6 per slide), let figures tell the story |
| Audience lost during design section | Add architecture walkthrough with progressive reveal |
| Evaluation slides overwhelming | Show 2–3 strongest figures, put rest in backup slides |
| Speaker notes too long | Target 3–4 sentences per slide, focus on transitions |
| Beamer compilation fails | Check figure paths, use \graphicspath{{figures/}} |
| PPTX looks different from Beamer | Adjust python-pptx font sizes and margins manually |