The goal of text-to-text generation is to make machines express like a human in many
applications such as conversation, summarization, and translation. It is one of the most …

The enormous quantity of text makes it challenging for users to obtain the key information
and knowledge. Automatic text summarization can alleviate this problem by providing …

A popular multimedia news format nowadays is providing users with a lively video and a
corresponding news article, which is employed by influential news media including CNN …

Multimodal summarization with multimodal output (MSMO) generates a summary with both
textual and visual content. Multimodal news report contains heterogeneous contents, which …

This paper studies learning from positive and unlabeled examples, known as PU learning. It
proposes a novel PU learning method called Predictive Adversarial Networks (PAN) based …

Automatic summarization plays an important role in the exponential document growth on the
Web. On content websites such as CNN. com and WikiHow. com, there often exist various …

The inference of ML models composed of diverse structures, types, and sizes boils down to
the execution of different dataflows (ie different tiling, ordering, parallelism, and shapes) …

In e-commerce portals, generating answers for product-related questions has become a
crucial task. In this article, we focus on the task of product-aware answer generation, which …

Relation classification is an essential and fundamental task in natural language processing.
Distant supervised methods have achieved great success on relation classification, which …

Stickers with vivid and engaging expressions are becoming increasingly popular in online
messaging apps, and some works are dedicated to automatically select sticker response by …