Dialogrpt Width

🚀 Demo

This project provides a demonstration of dialog response ranking. Please try this ✨ Colab Notebook Demo (click me!).

The width score predicts how likely the response is getting replied.

🚀 Quick Start

DialogRPT-width

Dialog Ranking Pretrained Transformers

How likely a dialog response is upvoted 😊 and/or gets replied 🔁?

This is what DialogRPT is learned to predict. It is a set of dialog response ranking models proposed by Microsoft Research NLP Group trained on 100 + millions of human feedback data. It can be used to improve existing dialog generation model (e.g., DialoGPT) by re-ranking the generated response candidates.

Quick Links:

• 📄 EMNLP'20 Paper
• 📊 Dataset, training, and evaluation
• 💻 Colab Notebook Demo

We considered the following tasks and provided corresponding pretrained models.

📞 Contact

Please create an issue on our repo.

📚 Citation

@inproceedings{gao2020dialogrpt,
    title={Dialogue Response RankingTraining with Large-Scale Human Feedback Data},
    author={Xiang Gao and Yizhe Zhang and Michel Galley and Chris Brockett and Bill Dolan},
    year={2020},
    booktitle={EMNLP}
}