8 citations · 9 across the 4 of their papers we have counts for
4 papers
Prompt Pool based Class-Incremental Continual Learning for Dialog State Tracking
Hong Liu, Yucheng Cai, Yuan Zhou +3
Continual learning is crucial for dialog state tracking (DST) in dialog systems, since requirements from users for new functionalities are often encountered. However, most of exist…
Knowledge-Retrieval Task-Oriented Dialog Systems with Semi-Supervision
Yucheng Cai, Hong Liu, Zhijian Ou +2
Most existing task-oriented dialog (TOD) systems track dialog states in terms of slots and values and use them to query a database to get relevant knowledge to generate responses.…
Advancing Semi-Supervised Task Oriented Dialog Systems by JSA Learning of Discrete Latent Variable Models
Yucheng Cai, Hong Liu, Zhijian Ou +2
Developing semi-supervised task-oriented dialog (TOD) systems by leveraging unlabeled dialog data has attracted increasing interests. For semi-supervised learning of latent state T…
A Challenge on Semi-Supervised and Reinforced Task-Oriented Dialog Systems
Zhijian Ou, Junlan Feng, Juanzi Li +5
A challenge on Semi-Supervised and Reinforced Task-Oriented Dialog Systems, Co-located with EMNLP2022 SereTOD Workshop.