35 citations · 98 across the 17 of their papers we have counts for
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cs.CL2019
Iterative Delexicalization for Improved Spoken Language Understanding
Avik Ray, Yilin Shen, Hongxia Jin
Recurrent neural network (RNN) based joint intent classification and slot tagging models have achieved tremendous success in recent years for building spoken language understanding…
cs.CL2019★ 4 cited
How Large a Vocabulary Does Text Classification Need? A Variational Approach to Vocabulary Selection
Wenhu Chen, Yu Su, Yilin Shen +3
With the rapid development in deep learning, deep neural networks have been widely adopted in many real-life natural language applications. Under deep neural networks, a pre-define…
cs.CV2019
Taking a HINT: Leveraging Explanations to Make Vision and Language Models More Grounded
Ramprasaath R. Selvaraju, Stefan Lee, Yilin Shen +5
Many vision and language models suffer from poor visual grounding - often falling back on easy-to-learn language priors rather than basing their decisions on visual concepts in the…