tools-only Paper2Web: Academic Homepage Generation
Overview
Paper2Web converts academic papers into interactive, explorable academic homepages. Unlike traditional approaches (direct generation, template-based, or HTML conversion), Paper2Web creates layout-aware, interactive websites through an iterative refinement process.
Core Capabilities
1. Layout-Aware Generation
- Analyzes paper structure and content organization
- Creates responsive, multi-section layouts
- Adapts design based on paper type (research article, review, preprint, etc.)
2. Interactive Elements
- Expandable sections for detailed content
- Interactive figures and tables
- Embedded citations and references
- Navigation menu for easy browsing
- Mobile-responsive design
3. Content Refinement
The system uses an iterative pipeline:
- Initial content extraction and structuring
- Layout generation with visual hierarchy
- Interactive element integration
- Aesthetic refinement
- Quality assessment and validation
Usage
Basic Website Generation
python pipeline_all.py \
--input-dir "path/to/papers" \
--output-dir "path/to/output" \
--model-choice 1
Parameters
--input-dir: Directory containing paper files (PDF or LaTeX)--output-dir: Directory for generated website files--model-choice: LLM model selection (1=GPT-4, 2=GPT-4.1)--enable-logo-search: Use Google Search API to find institution logos (optional)
Input Format Requirements
Supported Input Formats:
LaTeX source (preferred for best results)
- Main file:
main.tex - Include all referenced figures, tables, and bibliography files
- Organize in a single directory per paper
- Main file:
PDF files
- High-quality PDF with selectable text
- Embedded figures should be high resolution
- Proper section headers and structure
Directory Structure:
input/
└── paper_name/
├── main.tex # LaTeX source
├── bibliography.bib # References
├── figures/ # Figure files
│ ├── fig1.png
│ └── fig2.pdf
└── tables/ # Table files
Output Structure
Generated websites include:
output/paper_name/website/
├── index.html # Main webpage
├── styles.css # Styling
├── script.js # Interactive features
├── assets/ # Images and media
│ ├── figures/
│ └── logos/
└── data/ # Structured data (optional)
Customization Options
Visual Design
The generated websites automatically include:
- Professional color schemes based on paper content
- Typography optimized for readability
- Consistent spacing and visual hierarchy
- Dark mode support (optional)
Content Sections
Standard sections include:
- Abstract
- Key findings/contributions
- Methodology overview
- Results and visualizations
- Discussion and implications
- References and citations
- Author information and affiliations
Additional sections are automatically added based on paper content:
- Code repositories
- Dataset links
- Supplementary materials
- Related publications
Quality Assessment
Paper2Web includes built-in evaluation:
Aesthetic Metrics
- Layout balance and spacing
- Color harmony
- Typography consistency
- Visual hierarchy effectiveness
Informativeness Metrics
- Content completeness
- Key finding clarity
- Method explanation adequacy
- Results presentation quality
Technical Metrics
- Page load time
- Mobile responsiveness
- Browser compatibility
- Accessibility compliance
Advanced Features
Logo Discovery
When enabled with Google Search API:
- Automatically finds institution logos
- Matches author affiliations
- Downloads and optimizes logo images
- Integrates into website header
Citation Integration
- Interactive reference list
- Hover previews for citations
- Links to DOI and external sources
- Citation count tracking (if available)
Figure Enhancement
- High-resolution figure rendering
- Zoom and pan functionality
- Caption and description integration
- Multi-panel figure navigation
Best Practices
Input Preparation
- Use LaTeX when possible: Provides best structure extraction
- Include all assets: Figures, tables, and bibliography files
- Clean formatting: Remove compilation artifacts and temporary files
- High-quality figures: Use vector formats (PDF, SVG) when available
Model Selection
- GPT-4: Best balance of quality and cost
- GPT-4.1: Latest features, higher cost
- GPT-3.5-turbo: Faster processing, acceptable for simple papers
Output Optimization
- Review generated content for accuracy
- Check that all figures render correctly
- Test interactive elements functionality
- Verify mobile responsiveness
- Validate external links
Limitations
- Complex mathematical equations may require manual review
- Multi-column layouts in PDF may affect extraction quality
- Large papers (>50 pages) may require extended processing time
- Some specialized figure types may need manual adjustment
Integration with Other Components
Paper2Web can be combined with:
- Paper2Video: Generate companion video for the website
- Paper2Poster: Create matching poster design
- AutoPR: Generate promotional content linking to website