Multi-modal opinion summarization aims at automatically generating summaries of products
or businesses from multi-modal reviews containing text, image and table to present clear …

Nowadays, publishers like Elsevier increasingly use graphical abstracts (ie, a pictorial paper
summary) along with textual abstracts to facilitate scientific paper readings. In such a case …

Existing multimodal summarization approaches focus on fusing image features in the
encoding process, ignoring the individualized needs for images when generating different …

Pretrained language models (PLMs), especially large language models (LLMs) demonstrate
impressive capabilities in open-ended text generation. While our statistical results show that …

MultiModal Sentence Summarization (MMSS) aims to generate a brief summary based on
the given source sentence and its associated image. Previous studies on MMSS have …

Abstract Previous studies about MultiModal Summarization (MMS) mainly focus on effective
selection and filtering of visual features to assist in cross-modal fusion and text-based …

The increasing integration of multimedia such as videos and graphical abstracts in scientific
publications necessitates advanced summarization techniques. This paper introduces Uni …

This article focuses on the task of Multi-Modal Summarization with Multi-Modal Output for
China JD. COM e-commerce product description containing both source text and source …

MultiModal Summarization (MMS) aims to generate a concise summary based on
multimodal data like texts and images and has wide application in multimodal fields …

Natural Language Generation (NLG) has improved exponentially in recent years thanks to
the development of a large language model (LLM), this advancement has resulted in more …