360 citations · 467 across the 16 of their papers we have counts for
23 papers · 1 filter
Zero-Shot Aspect-Based Sentiment Analysis
Lei Shu, Hu Xu, Bing Liu +1
Aspect-based sentiment analysis (ABSA) typically requires in-domain annotated data for supervised training/fine-tuning. It is a big challenge to scale ABSA to a large number of new…
Zero-Shot Dialogue State Tracking via Cross-Task Transfer
Zhaojiang Lin, Bing Liu, Andrea Madotto +8
Zero-shot transfer learning for dialogue state tracking (DST) enables us to handle a variety of task-oriented dialogue domains without the expense of collecting in-domain data. In…
Leveraging Slot Descriptions for Zero-Shot Cross-Domain Dialogue State Tracking
Zhaojiang Lin, Bing Liu, Seungwhan Moon +7
Zero-shot cross-domain dialogue state tracking (DST) enables us to handle task-oriented dialogue in unseen domains without the expense of collecting in-domain data. In this paper,…
Continual Learning in Task-Oriented Dialogue Systems
Andrea Madotto, Zhaojiang Lin, Zhenpeng Zhou +6
Continual learning in task-oriented dialogue systems can allow us to add new domains and functionalities through time without incurring the high cost of a whole system retraining.…
Understanding Pre-trained BERT for Aspect-based Sentiment Analysis
Hu Xu, Lei Shu, Philip S. Yu +1
This paper analyzes the pre-trained hidden representations learned from reviews on BERT for tasks in aspect-based sentiment analysis (ABSA). Our work is motivated by the recent pro…
NUANCED: Natural Utterance Annotation for Nuanced Conversation with Estimated Distributions
Zhiyu Chen, Honglei Liu, Hu Xu +3
Existing conversational systems are mostly agent-centric, which assumes the user utterances would closely follow the system ontology (for NLU or dialogue state tracking). However,…