Dialogrpt Depth
DialogRPT-depth is a dialogue response ranking model developed by Microsoft Research, focusing on predicting the likelihood of dialogue responses sparking long discussion threads.
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Release Time : 3/2/2022
Model Overview
Trained on over 100 million pieces of human feedback data, this model evaluates the potential of dialogue responses to generate lengthy discussion threads and can optimize the response ranking of existing dialogue generation models.
Model Features
Large-scale Human Feedback Training
Trained on over 100 million real human dialogue feedback data, ensuring high practicality
Multi-dimensional Dialogue Evaluation
Capable of predicting not only upvotes (updown) but also reply counts (width) and discussion depth (depth)
Enhanced Dialogue Generation
Can be integrated with existing dialogue generation models (e.g., DialoGPT) to improve dialogue quality by reordering candidate responses
Model Capabilities
Dialogue Response Quality Assessment
Dialogue Response Ranking
Predicting Discussion Thread Length
Improving Dialogue Generation Models
Use Cases
Dialogue System Optimization
Chatbot Response Optimization
Ranks multiple candidate responses generated by chatbots to select the one most likely to spark in-depth discussions
Enhances user engagement and conversation depth
Social Media Interaction Analysis
Predicts the likelihood of social media comments sparking discussions
Helps content creators optimize interaction strategies
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