# DialogRPT-updown

### Dialog Ranking Pretrained Transformers

> How likely a dialog response is upvoted 👍 and/or gets replied 💬? 

This is what [**DialogRPT**](https://github.com/golsun/DialogRPT) is learned to predict.
It is a set of dialog response ranking models proposed by [Microsoft Research NLP Group](https://www.microsoft.com/en-us/research/group/natural-language-processing/) trained on 100 + millions of human feedback data. 
It can be used to improve existing dialog generation model (e.g., [DialoGPT](https://huggingface.co/microsoft/DialoGPT-medium)) by re-ranking the generated response candidates.

Quick Links:
* [EMNLP'20 Paper](https://arxiv.org/abs/2009.06978/)
* [Dataset, training, and evaluation](https://github.com/golsun/DialogRPT)
* [Colab Notebook Demo](https://colab.research.google.com/drive/1cAtfkbhqsRsT59y3imjR1APw3MHDMkuV?usp=sharing)

We considered the following tasks and provided corresponding pretrained models.

| Model card | Description  | 
| :-----------: | :----------- |
|   | **Given a context and its two human responses, predict...** | 
| [`microsoft/DialogRPT-updown`](https://huggingface.co/microsoft/DialogRPT-updown) |  ... which gets more upvotes?  | 
| [`microsoft/DialogRPT-width`](https://huggingface.co/microsoft/DialogRPT-width) | ... which gets more direct replies?  | 
| [`microsoft/DialogRPT-depth`](https://huggingface.co/microsoft/DialogRPT-depth) |  ... which gets longer follow-up thread? | 
|  | **Given a context and one human response, distinguish it with...**  |
| [`microsoft/DialogRPT-human-vs-rand`](https://huggingface.co/microsoft/DialogRPT-human-vs-rand) | ... a random human response  | 
| [`microsoft/DialogRPT-human-vs-machine`](https://huggingface.co/microsoft/DialogRPT-human-vs-machine) | ... a machine generated response  | 


### Examples:
The `updown` score predicts how likely the response is getting upvoted.

| Context | Response | `updown` score |
| :------ | :------- | :------------: |
| I love NLP! | Here’s a free textbook (URL) in case anyone needs it. | 0.613 |
| I love NLP! | Me too! | 0.111 |

### Contact:
Please create an issue on [our repo](https://github.com/golsun/DialogRPT)

### 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}
}
```