// 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.
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.
Provides guidance for automatically evolving and optimizing AI agents across any domain using LLM-driven evolution algorithms. Use when building self-improving agents, optimizing agent prompts and skills against benchmarks, or implementing automated agent evaluation loops.
| 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 |