Existing research on multimodal relation extraction (MRE) faces two co-existing challenges,
internal-information over-utilization and external-information under-exploitation. To combat …

Multimodal fusion focuses on integrating information from multiple modalities with the goal of
more accurate prediction, which has achieved remarkable progress in a wide range of …

This article studies the multimodal named entity recognition (MNER) and multimodal relation
extraction (MRE), which are important for content analysis and various applications. The …

Multimodal Aspect-based Sentiment Analysis (MABSA) is a fine-grained Sentiment Analysis
task, which has attracted growing research interests recently. Existing work mainly utilizes …

Identifying the owners of online devices on the Internet can enable numerous network
security applications. For example, fast and accurate Owner Name Entity Recognition …

The popularity of multimodal large language models (MLLMs) has triggered a recent surge
in research efforts dedicated to evaluating these models. Nevertheless, existing evaluation …

Multimodal information extraction is attracting research attention nowadays, which requires
aggregating representations from different modalities. In this paper, we present the Intra-and …

Extracting relational facts from multimodal data is a crucial task in the field of multimedia and
knowledge graphs that feeds into widespread real-world applications. The emphasis of …

Abstract Multimodal Aspect-Based Sentiment Analysis (MABSA) technology aims to utilize
both textual and visual modalities to achieve Multimodal Aspect Term Extraction (MATE) and …

Recently, multimodal information extraction has gained increasing attention in social media
understanding, as it helps to accomplish the task of information extraction by adding images …