We introduce PubMedQA, a novel biomedical question answering (QA) dataset collected
from PubMed abstracts. The task of PubMedQA is to answer research questions with …

Multi-label classification is an important yet challenging task in natural language processing.
It is more complex than single-label classification in that the labels tend to be correlated …

It is intuitive that NLP tasks for logographic languages like Chinese should benefit from the
use of the glyph information in those languages. However, due to the lack of rich …

We propose a new training objective named order-agnostic cross entropy (OaXE) for fully
non-autoregressive translation (NAT) models. OaXE improves the standard cross-entropy …

Existing text generation methods tend to produce repeated and” boring” expressions. To
tackle this problem, we propose a new text generation model, called Diversity-Promoting …

Segmenting a chunk of text into words is usually the first step of processing Chinese text, but
its necessity has rarely been explored. In this paper, we ask the fundamental question of …

Variational auto-encoders (VAEs) are widely used in natural language generation due to the
regularization of the latent space. However, generating sentences from the continuous latent …

Paraphrase generation is a longstanding important problem in natural language processing.
Recent progress in deep generative models has shown promising results on discrete latent …

Abstract Machine translation (namely MT) has been one of the most popular fields in
computational linguistics and Artificial Intelligence (AI). As one of the most promising …

Narrative story generation is a challenging problem because it demands the generated
sentences with tight semantic connections, which has not been well studied by most existing …