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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
[ICME 2026] Official implementation of Auto-Slides: An Interactive Multi-Agent System for Creating and Customizing Research Presentations
| Date | Stars |
|---|---|
| 2026-07-31 | 524 |
| 2026-08-01 | 524 |
| 2026-08-06 | 524 |
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<p align="center">
<h1 align="center">Auto-Slides: Automatic Academic Presentation Generation with Multi-Agent Collaboration</h1>
<p align="center">
<strong>Yuheng Yang</strong><sup>1</sup>
<strong>Wenjia Jiang</strong><sup>1</sup>
<strong>Yang Wang</strong><sup>1</sup>
<strong>Yiwei Wang</strong><sup>2</sup>
<strong>Chi Zhang</strong><sup>1</sup><sup>†</sup>
<br>
<sup>1</sup>AGI Lab, Westlake University
<sup>2</sup>University of California at Merced
<br>
<sup>†</sup>Corresponding author
<br>
<a href="mailto:[email protected]">[email protected]</a>
<br>
<a href='https://arxiv.org/abs/2509.11062'><img src='https://img.shields.io/badge/ArXiv-2509.11062-red'></a>
<a href='https://2026.ieeeicme.org/'><img src='https://img.shields.io/badge/ICME-2026%20Accepted-brightgreen'></a>
<a href='https://auto-slides.github.io/'><img src='https://img.shields.io/badge/Project-Page-green'></a>
<a href='https://github.com/wzsyyh/Auto-Slides'><img src='https://img.shields.io/badge/GitHub-Auto--Slides-blue'></a>
<br>
<img src="static/figures/teaser.png" width="100%">
</p>
<br>
</p>
Auto-Slides is an intelligent system that automatically converts academic research papers into well-structured, pedagogically optimized presentation slides. Built on large language models and cognitive science principles, it creates multimodal presentations with interactive customization capabilities.
## 🏗️ System Architecture
## 🚀 Features
- **Intelligent PDF Processing**: Automatically extracts text, figures, tables, and structure from research papers using advanced OCR and layout analysis
- **Multi-Agent Framework**: Employs specialized agents for content extraction, presentation planning, verification, and repair
- **Interactive Customization**: Supports real-time refinement through natural language dialogue
- **Pedagogical Optimization**: Creates presentation-oriented narratives that enhance learning and comprehension
- **Multimodal Output**: Generates slides with proper figure placement, table formatting, and code syntax highlighting
- **Multiple Themes**: Supports various Beamer themes (Madrid, Berlin, Singapore, etc.)
- **Bilingual Support**: Works with both English and Chinese papers
- **Speech Generation**: Optional accompanying speech script generation
## 📋 Requirements
- Python 3.8+
- LaTeX environment (TeX Live or MiKTeX)
- OpenAI API key
- 8GB+ RAM (for marker-pdf model)
## 🛠️ Installation
### 1. Clone the Repository
```bash
git clone https://github.com/your-username/auto-slides.git
cd auto-slides
```
### 2. Create Virtual Environment (Recommended)
```bash
python -m venv venv
source venv/bin/activate # Linux/Mac
# or
venv\Scripts\activate # Windows
```
### 3. Install Dependencies
```bash
pip install -r requirements.txt
```
### 4. Download Required Models
**Important**: Download the marker-pdf model for PDF processing:
```bash
python down_model.py
```
This will download the marker-pdf model to the `models/` directory (~2GB).
### 5. Configure API Keys
**Option 1: Use the provided template (Recommended)**
Rename the provided template file and add your API key:
```bash
# Rename the template file
mv ".env copy" .env
# Edit the .env file and add your OpenAI API key
nano .env # or use your preferred editor
```
**Option 2: Create from scratch**
Create a `.env` file in the project root:
```env
# OpenAI API Configuration (Required)
OPENAI_API_KEY=your_openai_api_key_here
# Optional: LangSmith for monitoring (uncomment if needed)
# LANGCHAIN_TRACING_V2="true"
# LANGCHAIN_ENDPOINT="https://api.smith.langchain.com"
# LANGCHAIN_API_KEY="your_langsmith_api_key_here"
# LANGCHAIN_PROExcerpt of 10,547 characters
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:1c2d70f1c033f495, desc:multi-agent, desc:multi agent