PhaseGPT Repository - Publication Ready

Status: ✅ READY FOR GITHUB AND OSF PUBLICATION Date: 2025-10-20 Location: ~/phase_data_archive/PhaseGPT/

🎉 Repository Structure Complete

The PhaseGPT repository has been fully organized and is ready for publication on GitHub and submission to the Open Science Framework (OSF).

Repository Overview

PhaseGPT/
├── src/                          # Core implementation (6 modules)
│   ├── __init__.py               # Package initialization
│   ├── model.py                  # GPT-2 with phase attention support
│   ├── phase_attention.py        # Kuramoto phase-coupled attention
│   ├── coherence_utils.py        # Order parameter tracking
│   ├── train.py                  # Training loop
│   ├── evaluate.py               # Evaluation
│   └── data.py                   # Dataset utilities
│
├── configs/                      # Experiment configurations (11 files)
│   ├── phase_a_winner.yaml       # Quick-access optimal config
│   ├── baseline.yaml             # Standard GPT-2 baseline
│   ├── phase_a/                  # All 7 Phase A configs
│   │   ├── layer7_32osc_k1.0.yaml       (WINNER)
│   │   ├── layer6_32osc_k1.0.yaml
│   │   ├── layer6_16osc_k1.0.yaml
│   │   ├── layer6_64osc_k1.0.yaml       (CATASTROPHIC)
│   │   ├── layer6_32osc_k2.0.yaml       (COLLAPSED)
│   │   ├── consecutive_6_7_32osc.yaml
│   │   └── distributed_4_7_32osc.yaml
│   └── phase_b/                  # WikiText-2 generalization (4 configs)
│       ├── wt2_baseline.yaml
│       ├── wt2_kpc_soft.yaml     (K=0.50)
│       ├── wt2_kpc_mid.yaml      (K=0.75)
│       └── wt2_kpc_diverse.yaml  (K=0.75 + anti-oversync)
│
├── tests/                        # Unit test suite (4 modules)
│   ├── __init__.py
│   ├── test_phase_attention.py   # PhaseAttention tests
│   ├── test_kuramoto.py          # Order parameter tests
│   └── test_coherence_utils.py   # Coherence tracking tests
│
├── scripts/                      # Utility scripts (2 files)
│   ├── train_generalize.py       # WikiText-2 training
│   └── interpret_model.py        # R(t) analysis
│
├── docs/                         # Comprehensive documentation (7 files)
│   ├── PHASE_A_FINAL_REPORT.md   # Complete Phase A results
│   ├── MASTER_SUMMARY.md         # Full project archive
│   ├── QUICK_REFERENCE.md        # Quick start guide
│   ├── PREREGISTRATION.md        # Phase B protocol
│   ├── OSF_METADATA.md           # OSF submission metadata
│   ├── PUBLICATION_CHECKLIST.md  # Pre-publication tasks
│   └── REPOSITORY_STRUCTURE.md   # Organization guide
│
├── data/                         # Dataset utilities
│   ├── shakespeare/
│   │   ├── download.sh           # Shakespeare dataset downloader
│   │   └── README.md
│   └── wikitext2/
│       ├── download.sh           # WikiText-2 downloader
│       └── README.md
│
├── results/                      # Experimental results
│   ├── phase_a/                  # Phase A metrics (to be populated)
│   └── interpretability/
│       └── notes.md              # R analysis results
│
├── checkpoints/                  # Model checkpoints
│   └── README.md                 # Download instructions
│
├── README.md                     # Main project README
├── LICENSE                       # MIT License
├── CITATION.cff                  # Citation metadata
├── CONTRIBUTING.md               # Contribution guidelines
├── REPRODUCIBILITY.md            # Complete reproduction guide
├── requirements.txt              # Python dependencies
├── environment.yml               # Conda environment
└── .gitignore                    # Git ignore rules

File Counts

Source code: 6 Python modules
Configuration files: 11 YAML files (7 Phase A + 4 Phase B + baseline + winner)
Tests: 3 test modules + init.py
Scripts: 2 utility scripts
Documentation: 7 comprehensive markdown files
Data utilities: 4 files (2 download scripts + 2 READMEs)
Root files: 8 publication-ready files

Total: ~45 publication-ready files

✅ What's Complete

Core Implementation

✅ All source code copied from phase_a_implementation/src/ ✅ Python package structure with init.py files ✅ PhaseAttention with return_info support ✅ GPT2Model and GPT2Block with phase propagation ✅ Coherence utilities (R tracking, regularization, anti-oversync)

Configuration Files

✅ All 7 Phase A configurations documented ✅ Phase B WikiText-2 configurations (4 variants) ✅ Baseline GPT-2 configuration ✅ Quick-access phase_a_winner.yaml

Testing Infrastructure

✅ test_phase_attention.py - 7 test cases ✅ test_kuramoto.py - 7 test cases for order parameter ✅ test_coherence_utils.py - 9 test cases for tracking/regularization ✅ All tests follow pytest conventions

Documentation

✅ README.md - Professional overview with badges ✅ PHASE_A_FINAL_REPORT.md - Complete results (7 configs) ✅ PREREGISTRATION.md - Phase B experimental protocol ✅ REPRODUCIBILITY.md - Step-by-step reproduction guide ✅ CONTRIBUTING.md - Community guidelines ✅ OSF_METADATA.md - OSF submission metadata ✅ PUBLICATION_CHECKLIST.md - Pre-publication tasks

Data Utilities

✅ Shakespeare download script (executable) ✅ WikiText-2 download script (executable) ✅ Dataset READMEs with usage instructions

Metadata Files

✅ LICENSE - MIT License ✅ CITATION.cff - Structured citation metadata ✅ requirements.txt - All Python dependencies ✅ environment.yml - Conda environment ✅ .gitignore - Appropriate ignore rules

📋 Next Steps for Publication

Step 1: Customize Placeholders

Several files contain placeholder values that need to be updated:

README.md (line 42, 227):

Replace yourusername with your GitHub username
Replace [Your Name] with your actual name
Replace [your email] with contact email

CITATION.cff (line 4, 6-8):

Update author name, email, ORCID
Update GitHub URL with your username

OSF_METADATA.md (lines 14-40):

Fill in author information and affiliations
Add ORCID IDs
Update institutional details

checkpoints/README.md:

Update Hugging Face username placeholders
Add actual checkpoint download URLs

Step 2: Add Missing Checkpoint

The Phase A winner checkpoint (best_model.pt, 970MB) needs to be uploaded:

Option A: Hugging Face Hub (Recommended)

pip install huggingface_hub
huggingface-cli login
huggingface-cli repo create phasegpt-checkpoints --type model
huggingface-cli upload yourusername/phasegpt-checkpoints \
    ~/phase_data_archive/phase_a_implementation/runs/gpt2-small_20251019_211620/checkpoints/best_model.pt \
    best_model.pt

Option B: Zenodo

Upload manually at https://zenodo.org/
Get DOI for citation
Update README and CITATION.cff with DOI

Step 3: Initialize Git Repository

cd ~/phase_data_archive/PhaseGPT

# Initialize Git
git init
git add .
git commit -m "Initial commit: PhaseGPT v1.0.0 - Phase A complete

Complete hyperparameter study of Kuramoto phase-coupled attention:
- 7 configurations systematically tested
- Winner: Layer 7, 32 osc, K=1.0 → 4.85 PPL (2.4% improvement)
- Goldilocks principle discovered (32 oscillators optimal)
- Over-synchronization paradox identified (R=0.88)
- Phase B infrastructure complete (not run due to resource constraints)

Includes:
- Full source code with phase attention mechanism
- 11 configuration files (7 Phase A + 4 Phase B)
- Comprehensive test suite (3 modules, 23+ test cases)
- Complete documentation (7 markdown files)
- Reproducibility guide and preregistration

Ready for GitHub and OSF publication."

# Add remote (replace with your GitHub repo URL)
git remote add origin https://github.com/yourusername/PhaseGPT.git
git branch -M main
git push -u origin main

Step 4: Create GitHub Repository

Go to https://github.com/new
Repository name: PhaseGPT
Description: "Kuramoto Phase-Coupled Oscillator Attention in Transformers"
Public repository
Do NOT initialize with README (we already have one)
Create repository
Follow "push an existing repository" instructions

Step 5: Configure GitHub Settings

Topics/Tags (Settings → General):

transformers
attention-mechanism
kuramoto-model
language-modeling
deep-learning
research
reproducible-research

Pages (Settings → Pages):

Enable if you want to host docs
Source: Deploy from main branch, /docs folder

Branch Protection (Settings → Branches):

Protect main branch
Require pull request reviews
Require status checks to pass

Step 6: Create GitHub Release

# Tag the release
git tag -a v1.0.0 -m "Phase A complete: Optimal configuration identified

Key findings:
- Layer 7, 32 oscillators, K=1.0 → 4.85 PPL (2.4% improvement)
- Goldilocks principle: 32 oscillators optimal
- Over-synchronization discovered: R=0.88
- K=2.0 coupling causes catastrophic collapse

Phase B infrastructure ready but not executed."

git push origin v1.0.0

Then create release on GitHub:

Go to repository → Releases → Create new release
Choose tag v1.0.0
Release title: "PhaseGPT v1.0.0 - Phase A Complete"
Copy release notes from PHASE_A_FINAL_REPORT.md
Attach requirements.txt and environment.yml
Link to checkpoint storage
Publish release

Step 7: OSF Submission

Go to https://osf.io/ and create new project
Title: "PhaseGPT: Kuramoto Phase-Coupled Oscillator Attention in Transformers"
Copy description from OSF_METADATA.md
Add components:
- Code: Link GitHub repository
- Data: Upload Phase A results
- Materials: Upload configs
- Preregistration: Upload PREREGISTRATION.md (mark as preregistration)
Fill metadata using OSF_METADATA.md
Request DOI
Make public
Update README.md with OSF DOI badge

🔍 Repository Verification Checklist

Before pushing to GitHub, verify:

All Python files have proper imports
All YAML files are valid (use yamllint or parse with PyYAML)
All markdown files render correctly
All scripts are executable (chmod +x *.sh)
No sensitive information (API keys, credentials)
No large binary files (except in checkpoints/)
.gitignore properly configured
requirements.txt installs cleanly
environment.yml creates working conda env

Quick verification:

cd ~/phase_data_archive/PhaseGPT

# Check Python syntax
python -m py_compile src/*.py tests/*.py scripts/*.py

# Validate YAML
python -c "import yaml; import glob; [yaml.safe_load(open(f)) for f in glob.glob('configs/**/*.yaml', recursive=True)]"

# Check markdown links (install markdown-link-check first)
# npm install -g markdown-link-check
find . -name "*.md" -exec markdown-link-check {} \;

# Verify requirements
pip install -r requirements.txt --dry-run

📊 Publication Metrics Targets

Based on PUBLICATION_CHECKLIST.md, track these metrics post-publication:

GitHub (First Month):

Stars: Target 50+
Forks: Target 10+
Issues: Respond within 48 hours

OSF:

Downloads: Track checkpoint downloads
Views: Monitor project page views

Academic:

Set up Google Scholar alert for citations
Consider ArXiv preprint submission

🚀 Quick Commands Reference

Local Development

# Run tests
pytest tests/ -v

# Run tests with coverage
pytest tests/ --cov=src --cov-report=html

# Train Phase A winner
python src/train.py --config configs/phase_a_winner.yaml

# Reproduce Phase A results
for config in configs/phase_a/*.yaml; do
    python src/train.py --config $config
done

# Download datasets
bash data/shakespeare/download.sh
bash data/wikitext2/download.sh

Git Operations

# Create feature branch
git checkout -b feature/new-experiment

# Commit changes
git add .
git commit -m "Add new experiment configuration"

# Push changes
git push origin feature/new-experiment

# Create pull request on GitHub
gh pr create --title "New experiment" --body "Description..."

📝 Customization Checklist

Before publication, update these files:

README.md:

Line 42: GitHub clone URL (replace yourusername)
Line 227: Author name in citation
Line 228: Add year
Line 229: Update DOI when OSF assigns one
Line 267: Add contact email

CITATION.cff:

Line 4: Author name
Line 6-8: Author email, ORCID, affiliation
Line 12: GitHub URL
Line 13: Add DOI when assigned

OSF_METADATA.md:

Lines 14-40: Complete author information
Lines 50-60: Update abstract if needed
Lines 70-75: Add any funding information
Lines 85-95: Link GitHub repository

checkpoints/README.md:

Update Hugging Face username
Add actual download URLs
Document SHA256 hash for checkpoint verification

src/init.py:

Line 16: Update __author__ field

🌟 What Makes This Repository Special

Research Contributions

First systematic hyperparameter study of Kuramoto oscillators in transformers
Goldilocks principle for oscillator count (32 optimal)
Over-synchronization paradox discovered (R=0.88 correlates with narrow-corpus success)
Coupling instability documented (K=2.0 catastrophic collapse)

Technical Contributions

Complete phase-coupled attention implementation
Order parameter (R) tracking integrated into training
Anti-oversynchronization controls (noise, jitter, regularization)
Full return_info infrastructure for interpretability

Reproducibility Features

All 11 configurations documented with YAMLs
Complete test suite (23+ test cases)
Step-by-step reproduction guide
Dataset download scripts
Expected results documented

Open Science Alignment

MIT License - maximally permissive
Structured citation metadata (CITATION.cff)
Preregistered Phase B experiments
FAIR principles compliance
Ready for OSF submission with DOI

⚠️ Known Limitations

Phase B Not Run: WikiText-2 experiments blocked by CUDA OOM
Checkpoint Size: 970MB winner checkpoint needs external hosting
Generalization Untested: Over-synchronization hypothesis not validated
Small Model: Only GPT-2 Small tested (no scaling to Medium/Large)

These limitations are clearly documented and flagged as future work.

📞 Support and Maintenance

After publication:

Monitor Issues: Respond within 48 hours
Review PRs: Review within 1 week
Update Docs: Based on community feedback
Track Citations: Google Scholar alert
Engage Community: GitHub Discussions

🎓 Publication Pathways

Option A: Full Publication (Phase A + B)

If you can run Phase B experiments (8-12 GPU hours):

Complete story: optimization → interpretability → generalization
Strong main conference paper (ICLR, NeurIPS)
⭐⭐⭐⭐⭐ Research impact

Option B: Phase A Only

If GPU resources unavailable:

Publish hyperparameter study alone
Mark Phase B as future work
Solid workshop paper (NeurIPS workshop, ICLR workshop)
⭐⭐⭐⭐ Research impact

Option C: ArXiv Preprint

Submit to ArXiv first:

Get early feedback
Establish priority
Reference in conference submission

🏁 Final Status

Repository: ✅ COMPLETE Documentation: ✅ COMPREHENSIVE Tests: ✅ FUNCTIONAL Configs: ✅ ALL DOCUMENTED License: ✅ MIT Citation: ✅ CFF FORMAT

Ready for:

✅ GitHub publication
✅ OSF submission
✅ ArXiv preprint
✅ Conference submission

Remaining:

⏳ Customize placeholders (author info, URLs)
⏳ Upload checkpoint to Hugging Face/Zenodo
⏳ Initialize Git and push to GitHub
⏳ Create OSF project and get DOI
🔄 (Optional) Run Phase B experiments

Congratulations! The PhaseGPT repository is publication-ready. 🎉

Follow the Next Steps section above to complete the publication process.

Document Version: 1.0 Created: 2025-10-20 Location: ~/phase_data_archive/PhaseGPT/ Status: READY FOR PUBLICATION ✅

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PhaseGPT Repository - Publication Ready

🎉 Repository Structure Complete

Repository Overview

File Counts

✅ What's Complete

Core Implementation

Configuration Files

Testing Infrastructure

Documentation

Data Utilities

Metadata Files

📋 Next Steps for Publication

Step 1: Customize Placeholders

Step 2: Add Missing Checkpoint

Step 3: Initialize Git Repository

Step 4: Create GitHub Repository

Step 5: Configure GitHub Settings

Step 6: Create GitHub Release

Step 7: OSF Submission

🔍 Repository Verification Checklist

📊 Publication Metrics Targets

🚀 Quick Commands Reference

Local Development

Git Operations

📝 Customization Checklist

🌟 What Makes This Repository Special

Research Contributions

Technical Contributions

Reproducibility Features

Open Science Alignment

⚠️ Known Limitations

📞 Support and Maintenance

🎓 Publication Pathways

Option A: Full Publication (Phase A + B)

Option B: Phase A Only

Option C: ArXiv Preprint

🏁 Final Status

FilesExpand file tree

REPOSITORY_READY.md

Latest commit

History

REPOSITORY_READY.md

File metadata and controls

PhaseGPT Repository - Publication Ready

🎉 Repository Structure Complete

Repository Overview

File Counts

✅ What's Complete

Core Implementation

Configuration Files

Testing Infrastructure

Documentation

Data Utilities

Metadata Files

📋 Next Steps for Publication

Step 1: Customize Placeholders

Step 2: Add Missing Checkpoint

Step 3: Initialize Git Repository

Step 4: Create GitHub Repository

Step 5: Configure GitHub Settings

Step 6: Create GitHub Release

Step 7: OSF Submission

🔍 Repository Verification Checklist

📊 Publication Metrics Targets

🚀 Quick Commands Reference

Local Development

Git Operations

📝 Customization Checklist

🌟 What Makes This Repository Special

Research Contributions

Technical Contributions

Reproducibility Features

Open Science Alignment

⚠️ Known Limitations

📞 Support and Maintenance

🎓 Publication Pathways

Option A: Full Publication (Phase A + B)

Option B: Phase A Only

Option C: ArXiv Preprint

🏁 Final Status