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Found 5 papers, 0 papers with code
Joint Goal Segmentation and Goal Success Prediction on Multi-Domain Conversations
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.
PersonaPKT: Building Personalized Dialogue Agents via Parameter-efficient Knowledge Transfer
Personalized dialogue agents (DAs) powered by large pre-trained language models (PLMs) often rely on explicit persona descriptions to maintain personality consistency.
KEPLET: Knowledge-Enhanced Pretrained Language Model with Topic Entity Awareness
In recent years, Pre-trained Language Models (PLMs) have shown their superiority by pre-training on unstructured text corpus and then fine-tuning on downstream tasks.
Large-scale Hybrid Approach for Predicting User Satisfaction with Conversational Agents
An widely used approach to tackle this is to collect human annotation data and use them for evaluation or modeling.
Knowledge Distillation from Internal Representations
In this paper, we propose to distill the internal representations of a large model such as BERT into a simplified version of it.
