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 …

Attention is an important mechanism that can be employed for a variety of deep learning
models across many different domains and tasks. This survey provides an overview of the …

Multimodal named entity recognition and relation extraction (MNER and MRE) is a
fundamental and crucial branch in information extraction. However, existing approaches for …

Recently multimodal named entity recognition (MNER) has utilized images to improve the
accuracy of NER in tweets. However, most of the multimodal methods use attention …

Multimodal named entity recognition (MNER) is a critical step in information extraction,
which aims to detect entity spans and classify them to corresponding entity types given a …

Multimodal named entity recognition (MNER) is a vision-language task where the system is
required to detect entity spans and corresponding entity types given a sentence-image pair …

With the development of social media, users increasingly tend to express their sentiments
(broadly including sentiment polarities, emotions and sarcasm, etc.) associated with fine …

Multimodal named entity extraction is an emerging task which uses both textual and visual
information to detect named entities and identify their entity types. The existing efforts are …

In this paper, we aim to explore an uncharted territory, which is Chinese multimodal named
entity recognition (NER) with both textual and acoustic contents. To achieve this, we …

Multimodal information extraction (MIE) gains significant attention as the popularity of
multimedia content increases. However, current MIE methods often resort to using task …