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  We considered the following tasks and provided corresponding pretrained models.
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- | Model card | Description |
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- | :-----------: | :----------- |
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- | | **Given a context and its two human responses, predict...** |
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- | [`microsoft/DialogRPT-updown`](https://huggingface.co/microsoft/DialogRPT-updown) | ... which gets more upvotes? |
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- | `microsoft/DialogRPT-width` (this model) | ... which gets more direct replies? |
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- | [`microsoft/DialogRPT-depth`](https://huggingface.co/microsoft/DialogRPT-depth) | ... which gets longer follow-up thread? |
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- | | **Given a context and one human response, distinguish it with...** |
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- | [`microsoft/DialogRPT-human-vs-rand`](https://huggingface.co/microsoft/DialogRPT-human-vs-rand) | ... a random human response |
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- | [`microsoft/DialogRPT-human-vs-machine`](https://huggingface.co/microsoft/DialogRPT-human-vs-machine) | ... a machine generated response |
 
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  ### Examples:
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- The `updown` score predicts how likely the response is getting upvoted.
 
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- | Context | Response | `updown` score |
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  | :------ | :------- | :------------: |
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- | I love NLP! | Here’s a free textbook (URL) in case anyone needs it. | 0.613 |
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- | I love NLP! | Me too! | 0.111 |
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  ### Contact:
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  Please create an issue on [our repo](https://github.com/golsun/DialogRPT)
 
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  We considered the following tasks and provided corresponding pretrained models.
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+ |Task | Description | Pretrained model |
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+ | :------------- | :----------- | :-----------: |
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+ | **Human feedback** | **given a context and its two human responses, predict...**|
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+ | `updown` | ... which gets more upvotes? | [model card](https://huggingface.co/microsoft/DialogRPT-updown) |
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+ | `width`| ... which gets more direct replies? | (this model) |
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+ | `depth`| ... which gets longer follow-up thread? | [model card](https://huggingface.co/microsoft/DialogRPT-width) |
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+ | **Human-like** (human vs fake) | **given a context and one human response, distinguish it with...** |
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+ | `human_vs_rand`| ... a random human response | [model card](https://huggingface.co/microsoft/DialogRPT-human-vs-rand) |
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+ | `human_vs_machine`| ... a machine generated response | [model card](https://huggingface.co/microsoft/DialogRPT-human-vs-machine) |
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  ### Examples:
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+ The `width` score predicts how likely the response is getting replied.
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+ Examples below can be reproduced with this [Colab Notebook](https://colab.research.google.com/drive/1cAtfkbhqsRsT59y3imjR1APw3MHDMkuV?usp=sharing)
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+ | Context | Response | `width` score |
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  | :------ | :------- | :------------: |
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+ | I love NLP! | Can anyone recommend a nice review paper? | 0.701 |
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+ | I love NLP! | Me too! | 0.029 |
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  ### Contact:
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  Please create an issue on [our repo](https://github.com/golsun/DialogRPT)