no code implementations • NAACL 2021 • Xiaoan Ding, Kevin Gimpel
Variational autoencoders (VAEs) are widely used for latent variable modeling of text.
1 code implementation • CONLL 2020 • Tianyu Liu, Xin Zheng, Xiaoan Ding, Baobao Chang, Zhifang Sui
The prior work on natural language inference (NLI) debiasing mainly targets at one or few known biases while not necessarily making the models more robust.
1 code implementation • EMNLP 2020 • Xiaoan Ding, Tianyu Liu, Baobao Chang, Zhifang Sui, Kevin Gimpel
We explore training objectives for discriminative fine-tuning of our generative classifiers, showing improvements over log loss fine-tuning from prior work .
no code implementations • IJCNLP 2019 • Xiaoan Ding, Kevin Gimpel
This model consistently outperforms both the generative and discriminative classifiers in small-data settings.
no code implementations • WS 2019 • Lifu Tu, Xiaoan Ding, Dong Yu, Kevin Gimpel
We propose a simple and effective modeling framework for controlled generation of multiple, diverse outputs.