Dialogrpt Updown
DialogRPT-updown is a dialogue response ranking model trained on human feedback data, predicting the likelihood of a dialogue response receiving likes.
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Release Time : 3/2/2022
Model Overview
DialogRPT-updown is one of the dialogue response ranking models proposed by Microsoft Research NLP group, trained on over 100 million human feedback data points. It can be used to improve existing dialogue generation models by re-ranking generated response candidates.
Model Features
Large-scale Human Feedback Training
Trained on over 100 million human feedback data points, capable of accurately predicting the popularity of dialogue responses.
Improving Dialogue Generation Models
Can be used to enhance existing dialogue generation models by re-ranking generated response candidates.
Multi-task Support
In addition to the updown task, it also supports different human feedback prediction tasks such as width and depth.
Model Capabilities
Dialogue Response Ranking
Predicting Like Probability
Improving Dialogue Generation Models
Use Cases
Dialogue Systems
Enhancing Chatbot Responses
Using DialogRPT-updown to re-rank multiple response candidates generated by a chatbot, selecting the response most likely to receive user likes.
Improves user satisfaction and interaction quality
Social Media Interaction Analysis
Predicting the popularity of dialogue responses on social media to help content creators optimize interaction strategies.
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