6 citations · 7 across the 3 of their papers we have counts for
3 papers
cs.CL2019★ 1 cited
Variational Sequential Labelers for Semi-Supervised Learning
Mingda Chen, Qingming Tang, Karen Livescu +1
We introduce a family of multitask variational methods for semi-supervised sequence labeling. Our model family consists of a latent-variable generative model and a discriminative l…
cs.CL2019
Smaller Text Classifiers with Discriminative Cluster Embeddings
Mingda Chen, Kevin Gimpel
Word embedding parameters often dominate overall model sizes in neural methods for natural language processing. We reduce deployed model sizes of text classifiers by learning a har…
cs.CL2019★ 6 cited
Controllable Paraphrase Generation with a Syntactic Exemplar
Mingda Chen, Qingming Tang, Sam Wiseman +1
Prior work on controllable text generation usually assumes that the controlled attribute can take on one of a small set of values known a priori. In this work, we propose a novel t…