Bin Guo


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PersonaPKT: Building Personalized Dialogue Agents via Parameter-efficient Knowledge Transfer
Xu Han | Bin Guo | Yoon Jung | Benjamin Yao | Yu Zhang | Xiaohu Liu | Chenlei Guo
Proceedings of The Fourth Workshop on Simple and Efficient Natural Language Processing (SustaiNLP)


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Joint Goal Segmentation and Goal Success Prediction on Multi-Domain Conversations
Meiguo Wang | Benjamin Yao | Bin Guo | Xiaohu Liu | Yu Zhang | Tuan-Hung Pham | Chenlei Guo
Proceedings of the 29th International Conference on Computational Linguistics

To evaluate the performance of a multi-domain goal-oriented Dialogue System (DS), it is important to understand what the users’ goals are for the conversations and whether those goals are successfully achieved. The success rate of goals directly correlates with user satisfaction and perceived usefulness of the DS. In this paper, we propose a novel automatic dialogue evaluation framework that jointly performs two tasks: goal segmentation and goal success prediction. We extend the RoBERTa-IQ model (Gupta et al., 2021) by adding multi-task learning heads for goal segmentation and success prediction. Using an annotated dataset from a commercial DS, we demonstrate that our proposed model reaches an accuracy that is on-par with single-pass human annotation comparing to a three-pass gold annotation benchmark.