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William Hogan
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Fine-grained contrastive learning for relation extraction
W Hogan, J Li, J Shang
arXiv preprint arXiv:2205.12491, 2022
102022
Abstractified Multi-instance Learning (AMIL) for Biomedical Relation Extraction
WP Hogan, M Huang, Y Katsis, T Baldwin, HC Kim, Y Baeza, A Bartko, ...
3rd Conference on Automated Knowledge Base Construction, 2021
72021
An overview of distant supervision for relation extraction with a focus on denoising and pre-training methods
W Hogan
arXiv preprint arXiv:2207.08286, 2022
62022
Dail: Data augmentation for in-context learning via self-paraphrase
D Li, Y Li, D Mekala, S Li, X Wang, W Hogan, J Shang
arXiv preprint arXiv:2311.03319, 2023
42023
Open-world Semi-supervised Generalized Relation Discovery Aligned in a Real-world Setting
W Hogan, J Li, J Shang
EMNLP 2023, 16, 2023
32023
BLAR: Biomedical Local Acronym Resolver
W Hogan, YV Baeza, Y Katsis, T Baldwin, HC Kim, C Hsu
ACL, Proceedings of the 20th Workshop on Biomedical Language Processing, 126-130, 2021
32021
READ: Improving Relation Extraction from an ADversarial Perspective
D Li, W Hogan, J Shang
arXiv preprint arXiv:2404.02931, 2024
2024
Normalization of Predominant and Long-tail Bacterial Entities with a Hybrid CNN-LSTM and Knowledge-Driven Model
W Hogan, R Mehta, Y Vazquez-Baeza, Y Katsis, HC Kim, CN Hsu
AKBC, Proceedings of the SciNLP Workshop: Natural Language Processing and …, 2020
2020
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Articles 1–8