2022年3月23日 Unified Structure Generation for Universal Information Extraction. Yaojie Lu, Qing Liu, Dai Dai, Xinyan Xiao, Hongyu Lin, Xianpei Han, Le Sun, Hua Wu. Information extraction suffers from its varying targets, heterogeneous structures, and demand-specific schemas.
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2024年8月23日 To address this, this work for the first time introduces the concept of grounded Multimodal Universal Information Extraction (MUIE), providing a unified task framework to analyze any IE tasks over various modalities, along with their fine-grained groundings.
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2023年1月9日 Universal Information Extraction as Unified Semantic Matching. Jie Lou, Yaojie Lu, Dai Dai, Wei Jia, Hongyu Lin, Xianpei Han, Le Sun, Hua Wu. The challenge of information extraction (IE) lies in the diversity of label schemas and the heterogeneity of structures.
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2024年6月6日 Abstract: 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 recognizing and analyzing cross-modal information. To address this, this work for the first time introduces the concept of grounded Multimodal Universal ...
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An architecture is proposed that, focusing on the Wikipedia as a textual repository, aims at enriching it with semantic information in an automatic way. This approach combines linguistic processing, Word Sense Disambiguation and Relation Extraction ...
More2022年3月23日 Unified Structure Generation for Universal Information Extraction. Yaojie Lu, Qing Liu, Dai Dai, Xinyan Xiao, Hongyu Lin, Xianpei Han, Le Sun, Hua Wu. Information extraction suffers from its varying targets, heterogeneous structures, and demand-specific schemas.
More2024年8月23日 To address this, this work for the first time introduces the concept of grounded Multimodal Universal Information Extraction (MUIE), providing a unified task framework to analyze any IE tasks over various modalities, along with their fine-grained groundings.
More2023年1月9日 Universal Information Extraction as Unified Semantic Matching. Jie Lou, Yaojie Lu, Dai Dai, Wei Jia, Hongyu Lin, Xianpei Han, Le Sun, Hua Wu. The challenge of information extraction (IE) lies in the diversity of label schemas and the heterogeneity of structures.
More2024年6月6日 Abstract: 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 recognizing and analyzing cross-modal information. To address this, this work for the first time introduces the concept of grounded Multimodal Universal ...
MoreAn architecture is proposed that, focusing on the Wikipedia as a textual repository, aims at enriching it with semantic information in an automatic way. This approach combines linguistic processing, Word Sense Disambiguation and Relation Extraction ...
More2022年3月23日 Unified Structure Generation for Universal Information Extraction. Yaojie Lu, Qing Liu, Dai Dai, Xinyan Xiao, Hongyu Lin, Xianpei Han, Le Sun, Hua Wu. Information extraction suffers from its varying targets, heterogeneous structures, and demand-specific schemas.
More2024年8月23日 To address this, this work for the first time introduces the concept of grounded Multimodal Universal Information Extraction (MUIE), providing a unified task framework to analyze any IE tasks over various modalities, along with their fine-grained groundings.
More2023年1月9日 Universal Information Extraction as Unified Semantic Matching. Jie Lou, Yaojie Lu, Dai Dai, Wei Jia, Hongyu Lin, Xianpei Han, Le Sun, Hua Wu. The challenge of information extraction (IE) lies in the diversity of label schemas and the heterogeneity of structures.
More2024年6月6日 Abstract: 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 recognizing and analyzing cross-modal information. To address this, this work for the first time introduces the concept of grounded Multimodal Universal ...
MoreAn architecture is proposed that, focusing on the Wikipedia as a textual repository, aims at enriching it with semantic information in an automatic way. This approach combines linguistic processing, Word Sense Disambiguation and Relation Extraction ...
More
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