350 citations · 437 across the 18 of their papers we have counts for
5 papers · 1 filter
C2C-GenDA: Cluster-to-Cluster Generation for Data Augmentation of Slot Filling
Yutai Hou, Sanyuan Chen, Wanxiang Che +2
Slot filling, a fundamental module of spoken language understanding, often suffers from insufficient quantity and diversity of training data. To remedy this, we propose a novel Clu…
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…
Recall and Learn: Fine-tuning Deep Pretrained Language Models with Less Forgetting
Sanyuan Chen, Yutai Hou, Yiming Cui +3
Deep pretrained language models have achieved great success in the way of pretraining first and then fine-tuning. But such a sequential transfer learning paradigm often confronts t…