模型:

microsoft/DialogRPT-depth

英文

演示

请尝试这个 ➤➤➤ Colab Notebook Demo (click me!)

Context Response depth score
I love NLP! Can anyone recommend a nice review paper? 0.724
I love NLP! Me too! 0.032

深度分数预测回应有多大可能导致长时间的跟进讨论线程。

DialogRPT-depth

对话排序预训练变换器

对话回应有多大可能被点赞 ? 和/或得到回复 ??

这是 DialogRPT 学习预测的内容。它是由 Microsoft Research NLP Group 提出的一组对话回应排序模型,通过对 100+ 万条人类反馈数据进行训练。它可以用来改进现有的对话生成模型(例如 DialoGPT ),通过重新排序生成的回应候选项。

快速链接:

我们考虑了以下任务,并提供了相应的预训练模型。

Task Description Pretrained model
Human feedback given a context and its two human responses, predict...
updown ... which gets more upvotes? 1238321
width ... which gets more direct replies? 1239321
depth ... which gets longer follow-up thread? this model
Human-like (human vs fake) given a context and one human response, distinguish it with...
human_vs_rand ... a random human response 12310321
human_vs_machine ... a machine generated response 12311321

联系方式:

请在 our repo 上创建一个问题。

引用:

@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}
}