Chain-of-thought prompt distillation for multimodal named entity and multimodal relation extraction

F Chen, Y Feng - arxiv preprint arxiv:2306.14122, 2023 - arxiv.org
Multimodal Named Entity Recognition (MNER) and Multimodal Relation Extraction (MRE)
necessitate the fundamental reasoning capacity for intricate linguistic and multimodal …

A novel feature integration and entity boundary detection for named entity recognition in cybersecurity

X Wang, J Liu - Knowledge-Based Systems, 2023 - Elsevier
Owing to continuous cyberattacks, a large amount of threat intelligence is generated online
every day. However, threat intelligence is mostly unstructured and multisource …

Multi-granularity cross-modal representation learning for named entity recognition on social media

P Liu, G Wang, H Li, J Liu, Y Ren, H Zhu… - Information Processing & …, 2024 - Elsevier
With social media posts tending to be multimodal, Multimodal Named Entity Recognition
(MNER) for the text with its accompanying image is attracting more and more attention since …

Context-ner: Contextual phrase generation at scale

H Gupta, S Verma, S Mashetty, S Mishra - arxiv preprint arxiv:2109.08079, 2021 - arxiv.org
Named Entity Recognition (NER) has seen significant progress in recent years, with
numerous state-of-the-art (SOTA) models achieving high performance. However, very few …

[HTML][HTML] An adaptive approach to noisy annotations in scientific information extraction

N Bölücü, M Rybinski, X Dai, S Wan - Information Processing & …, 2024 - Elsevier
Despite recent advances in large language models (LLMs), the best effectiveness in
information extraction (IE) is still achieved by fine-tuned models, hence the need for …

A Positive-Unlabeled Metric Learning Framework for Document-Level Relation Extraction with Incomplete Labeling

Y Wang, H Pan, T Zhang, W Wu, W Hu - Proceedings of the AAAI …, 2024 - ojs.aaai.org
The goal of document-level relation extraction (RE) is to identify relations between entities
that span multiple sentences. Recently, incomplete labeling in document-level RE has …

Exogenous and Endogenous Data Augmentation for Low-Resource Complex Named Entity Recognition

X Zhang, G Chen, S Cui, J Sheng, T Liu… - Proceedings of the 47th …, 2024 - dl.acm.org
Low-resource Complex Named Entity Recognition aims to detect entities with the form of any
linguistic constituent under scenarios with limited manually annotated data. Existing studies …

Multi-level semantic enhancement based on self-distillation BERT for Chinese named entity recognition

Z Li, S Cao, M Zhai, N Ding, Z Zhang, B Hu - Neurocomputing, 2024 - Elsevier
As an important foundational task in the field of natural language processing, the Chinese
named entity recognition (NER) task has received widespread attention in recent years. Self …

Uncertainty-Aware Contrastive Learning for semi-supervised named entity recognition

K Yang, Z Yang, S Zhao, Z Yang, S Zhang… - Knowledge-Based …, 2024 - Elsevier
Named entity recognition (NER) based on deep neural networks has shown competitive
performance when trained on large-scale human-annotated data. However, they face …

Improving distantly supervised named entity recognition by emphasizing uncertain examples

B Nie, Y Shao, Y Wang - Pattern Analysis and Applications, 2025 - Springer
Distantly supervised named entity recognition (DS-NER) aims to acquire knowledge from
noisy labels. Recently, label re-weighting and label correction based frameworks have been …