5 citations · 5 across the 5 of their papers we have counts for
5 papers
Code-MIE: A Code-style Model for Multimodal Information Extraction with Scene Graph and Entity Attribute Knowledge Enhancement
Jiang Liu, Ge Qiu, Hao Fei +5
With the rapid development of large language models (LLMs), more and more researchers have paid attention to information extraction based on LLMs. However, there are still some spa…
Event Extraction in Large Language Model
Bobo Li, Xudong Han, Jiang Liu +11
Large language models (LLMs) and multimodal LLMs are changing event extraction (EE): prompting and generation can often produce structured outputs in zero shot or few shot settings…
Multi-Granular Multimodal Clue Fusion for Meme Understanding
Li Zheng, Hao Fei, Ting Dai +5
With the continuous emergence of various social media platforms frequently used in daily life, the multimodal meme understanding (MMU) task has been garnering increasing attention.…
MD: A Multimodal, Multilingual and Multitask Dataset for Grounded Document-level Information Extraction
Jiang Liu, Bobo Li, Xinran Yang +5
Multimodal information extraction (IE) tasks have attracted increasing attention because many studies have shown that multimodal information benefits text information extraction. H…
Recognizing Everything from All Modalities at Once: Grounded Multimodal Universal Information Extraction
Meishan Zhang, Hao Fei, Bin Wang +4
In the field of information extraction (IE), tasks across a wide range of modalities and their combinations have been traditionally studied in isolation, leaving a gap in deeply re…