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Multimodal Named Entity Recognition (MNER) and Multimodal Relation Extraction (MRE) necessitate the fundamental reasoning capacity for intricate linguistic and multimodal comprehension.
Visual attention model for name tagging in multimodal social media
Di Lu, Leonardo Neves, Vitor Carvalho, Ning Zhang, and Heng Ji. 2018 · 1999
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Flat: Chinese ner using flat-lattice transformer
Xiaonan Li, Hang Yan, Xipeng Qiu, and Xuanjing Huang. 2020 · 2004
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Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, T. J. Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeff Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2005
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Local additivity based data augmentation for semi-supervised ner
Jiaao Chen, Zhenghui Wang, Ran Tian, Zichao Yang, and Diyi Yang. 2020 · 2010
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Adaptive co-attention network for named entity recognition in tweets
Qi Zhang, Jinlan Fu, Xiaoyu Liu, and Xuanjing Huang. 2018 · 2018
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TOI-CNN: a solution of information extraction on Chinese insurance policy
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Improving multimodal named entity recognition via entity span detection with unified multimodal transformer
Jianfei Yu, Jing Jiang, Li Yang, and Rui Xia. 2020 · 2020
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Data augmentation for cross-domain named entity recognition
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Knowledge distillation: A survey
Jianping Gou, Baosheng Yu, Stephen J Maybank, and Dacheng Tao. 2021 · 2021
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Open hierarchical relation extraction
Ruobing Xie Xu Han Zhiyuan Liu Fen Lin Leyu Lin Maosong Sun Kai Zhang, Yuan Yao. 2021 · 2021
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Prefix-tuning: Optimizing continuous prompts for generation
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Learning transferable visual models from natural language supervision
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Chain of thought prompting elicits reasoning in large language models
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Robust self-augmentation for named entity recognition with meta reweighting
Linzhi Wu, Pengjun Xie, Jie Zhou, Meishan Zhang, Ma Chunping, Guangwei Xu, and Min Zhang. 2022 · 2022
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Maf: A general matching and alignment framework for multimodal named entity recognition
Bo Xu, Shizhou Huang, Chaofeng Sha, and Hongya Wang. 2022 · 2022
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Learning from different text-image pairs: A relation-enhanced graph convolutional network for multimodal ner
Fei Zhao, Chunhui Li, Zhen Wu, Shangyu Xing, and Xinyu Dai. 2022 · 2022
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Aligning instruction tasks unlocks large language models as zero-shot relation extractors
Yu Su Kai Zhang, Bernal Jiménez Gutiérrez. 2023 · 2023
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Xiang Chen, Ningyu Zhang, Lei Li, Shumin Deng, Chuanqi Tan, Changliang Xu, Fei Huang, Luo Si, and Huajun Chen. 2022 · 2022
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Large language models are zero-shot reasoners
Takeshi Kojima, Shixiang Shane Gu, Machel Reid, Yutaka Matsuo, and Yusuke Iwasawa. 2022 · 2022
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Flat multi-modal interaction transformer for named entity recognition
Junyu Lu, Dixiang Zhang, and Pingjian Zhang. 2022 · 2022
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Bo Li, Gexiang Fang, Yang Yang, Quansen Wang, Wei Ye, Wen Zhao, and Shikun Zhang. 2023a
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Junnan Li, Dongxu Li, Silvio Savarese, and Steven Hoi. 2023b
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Named entity and relation extraction with multi-modal retrieval
Xinyu Wang, Jiong Cai, Yong Jiang, Pengjun Xie, Kewei Tu, and Wei Lu. 2022a
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Ita: Image-text alignments for multi-modal named entity recognition
Xinyu Wang, Min Gui, Yong Jiang, Zixia Jia, Nguyen Bach, Tao Wang, Zhongqiang Huang, Fei Huang, and Kewei Tu. 2021a
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