A survey on deep learning for named entity recognition

J Li, A Sun, J Han, C Li - IEEE transactions on knowledge and …, 2020 - ieeexplore.ieee.org
Named entity recognition (NER) is the task to identify mentions of rigid designators from text
belonging to predefined semantic types such as person, location, organization etc. NER …

A survey on multimodal bidirectional machine learning translation of image and natural language processing

W Nam, B Jang - Expert Systems with Applications, 2024 - Elsevier
Advances in multimodal machine learning help artificial intelligence to resemble human
intellect more closely, which perceives the world from multiple modalities. We surveyed state …

Hybrid transformer with multi-level fusion for multimodal knowledge graph completion

X Chen, N Zhang, L Li, S Deng, C Tan, C Xu… - Proceedings of the 45th …, 2022 - dl.acm.org
Multimodal Knowledge Graphs (MKGs), which organize visual-text factual knowledge, have
recently been successfully applied to tasks such as information retrieval, question …

Bi-bimodal modality fusion for correlation-controlled multimodal sentiment analysis

W Han, H Chen, A Gelbukh, A Zadeh… - Proceedings of the …, 2021 - dl.acm.org
Multimodal sentiment analysis aims to extract and integrate semantic information collected
from multiple modalities to recognize the expressed emotions and sentiment in multimodal …

Opendialkg: Explainable conversational reasoning with attention-based walks over knowledge graphs

S Moon, P Shah, A Kumar, R Subba - Proceedings of the 57th …, 2019 - aclanthology.org
We study a conversational reasoning model that strategically traverses through a large-
scale common fact knowledge graph (KG) to introduce engaging and contextually diverse …

Good visual guidance makes a better extractor: Hierarchical visual prefix for multimodal entity and relation extraction

X Chen, N Zhang, L Li, Y Yao, S Deng, C Tan… - arXiv preprint arXiv …, 2022 - arxiv.org
Multimodal named entity recognition and relation extraction (MNER and MRE) is a
fundamental and crucial branch in information extraction. However, existing approaches for …

Multi-modal graph fusion for named entity recognition with targeted visual guidance

D Zhang, S Wei, S Li, H Wu, Q Zhu… - Proceedings of the AAAI …, 2021 - ojs.aaai.org
Multi-modal named entity recognition (MNER) aims to discover named entities in free text
and classify them into pre-defined types with images. However, dominant MNER models do …

Improving multimodal named entity recognition via entity span detection with unified multimodal transformer

J Yu, J Jiang, L Yang, R Xia - 2020 - ink.library.smu.edu.sg
In this paper, we study Multimodal Named Entity Recognition (MNER) for social media posts.
Existing approaches for MNER mainly suffer from two drawbacks:(1) despite generating …

RpBERT: a text-image relation propagation-based BERT model for multimodal NER

L Sun, J Wang, K Zhang, Y Su, F Weng - Proceedings of the AAAI …, 2021 - ojs.aaai.org
Recently multimodal named entity recognition (MNER) has utilized images to improve the
accuracy of NER in tweets. However, most of the multimodal methods use attention …

Nbias: A natural language processing framework for BIAS identification in text

S Raza, M Garg, DJ Reji, SR Bashir, C Ding - Expert Systems with …, 2024 - Elsevier
Bias in textual data can lead to skewed interpretations and outcomes when the data is used.
These biases could perpetuate stereotypes, discrimination, or other forms of unfair …