10 citations · 24 across the 8 of their papers we have counts for
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cs.CL2022
GL-CLeF: A Global-Local Contrastive Learning Framework for Cross-lingual Spoken Language Understanding
Libo Qin, Qiguang Chen, Tianbao Xie +4
Due to high data demands of current methods, attention to zero-shot cross-lingual spoken language understanding (SLU) has grown, as such approaches greatly reduce human annotation…
cs.CL2022★ 2 cited
UniDU: Towards A Unified Generative Dialogue Understanding Framework
Zhi Chen, Lu Chen, Bei Chen +5
With the development of pre-trained language models, remarkable success has been witnessed in dialogue understanding (DU). However, current DU approaches usually employ independent…
cs.CL2022
Text is no more Enough! A Benchmark for Profile-based Spoken Language Understanding
Xiao Xu, Libo Qin, Kaiji Chen +3
Current researches on spoken language understanding (SLU) heavily are limited to a simple setting: the plain text-based SLU that takes the user utterance as input and generates its…