Mingda Chen

Controllable Paraphrase Generation with a Syntactic Exemplar

2019

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 task, where the …

ALBERT: A Lite BERT for Self-supervised Learning of Language Representations

2019 · arXiv (Cornell University)

Increasing model size when pretraining natural language representations often results in improved performance on downstream tasks. However, at some point further model increases become harder due to GPU/TPU memory limitations and longer training times. To …