13 citations · 22 across the 4 of their papers we have counts for
4 papers
Learning to Bridge Metric Spaces: Few-shot Joint Learning of Intent Detection and Slot Filling
Yutai Hou, Yongkui Lai, Cheng Chen +2
In this paper, we investigate few-shot joint learning for dialogue language understanding. Most existing few-shot models learn a single task each time with only a few examples. How…
Few-shot Learning for Multi-label Intent Detection
Yutai Hou, Yongkui Lai, Yushan Wu +2
In this paper, we study the few-shot multi-label classification for user intent detection. For multi-label intent detection, state-of-the-art work estimates label-instance relevanc…
FewJoint: A Few-shot Learning Benchmark for Joint Language Understanding
Yutai Hou, Jiafeng Mao, Yongkui Lai +4
Few-shot learning (FSL) is one of the key future steps in machine learning and has raised a lot of attention. However, in contrast to the rapid development in other domains, such a…
Few-shot Slot Tagging with Collapsed Dependency Transfer and Label-enhanced Task-adaptive Projection Network
Yutai Hou, Wanxiang Che, Yongkui Lai +4
In this paper, we explore the slot tagging with only a few labeled support sentences (a.k.a. few-shot). Few-shot slot tagging faces a unique challenge compared to the other few-sho…