Multimodal machine learning is a vibrant multi-disciplinary research field that aims to design
computer agents with intelligent capabilities such as understanding, reasoning, and learning …

Multimodal machine learning is a vibrant multi-disciplinary research field that aims to design
computer agents with intelligent capabilities such as understanding, reasoning, and learning …

In this paper, we introduce How2, a multimodal collection of instructional videos with English
subtitles and crowdsourced Portuguese translations. We also present integrated sequence …

Summarization, is to reduce the size of the document while preserving the meaning, is one
of the most researched areas among the Natural Language Processing (NLP) community …

The new era of technology has brought us to the point where it is convenient for people to
share their opinions over an abundance of platforms. These platforms have a provision for …

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

Visual text analytics has recently emerged as one of the most prominent topics in both
academic research and the commercial world. To provide an overview of the relevant …

Rapid growth of multi-modal documents on the Internet makes multi-modal summarization
research necessary. Most previous research summarizes texts or images separately. Recent …

We present a system that automatically transforms text articles into audio-visual slideshows
by leveraging the notion of word concreteness, which measures how strongly a word or …

Cross-modal contrastive learning in vision language pretraining (VLP) faces the challenge
of (partial) false negatives. In this paper, we study this problem from the perspective of …