Helping humans ride the GenAI evaluation wave
Project description
GLIDE
Generative Label Inference & Debiasing Engine
🧭 What is GLIDE?
GLIDE is a Python library for rigorous evaluation of GenAI systems using hybrid human/proxy annotations.
🤔 Why GLIDE?
- 🤖 GenAI applications are everywhere — and imperfect. Deployed systems make mistakes, and measuring how often matters.
- ⚖️ LLM-as-judge is biased. Proxy evaluators (models, heuristics) are cheap but systematically over- or under-estimate true performance.
- 🧑 Rigorous evaluation requires a human in the loop. Ground-truth labels from humans are expensive, so only a small subset is feasible.
- 📐 GLIDE bridges the gap. It combines a small set of human annotations with a large set of proxy predictions to produce statistically valid metrics — correcting proxy bias without requiring full human labeling.
⚡ Quick Start
🚧 Coming soon — see the documentation.
📚 Documentation
🚧 Documentation link coming soon.
🤝 Contributing
Contributions are welcome! Feel free to open an issue to report a bug or suggest a feature, or submit a pull request with your changes.
🔢 Versioning
This project follows Semantic Versioning (SemVer): MAJOR.MINOR.PATCH.
📦 Dependency Support
This project follows SPEC 0 for dependency support windows.
📄 License & Citation
This project is licensed under the Apache 2.0 License.
If you use Glide in your research, please cite:
@software{glide,
title = {GLIDE: Generative Label Inference \& Debiasing Engine},
year = {2026},
url = {https://github.com/EmertonData/glide},
}
🏛️ Affiliation
Developed at Emerton Data.
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