Fine-grained contrastive learning for relation extraction W Hogan, J Li, J Shang arXiv preprint arXiv:2205.12491, 2022 | 10 | 2022 |
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 | 7 | 2021 |
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 | 6 | 2022 |
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 | 4 | 2023 |
Open-world Semi-supervised Generalized Relation Discovery Aligned in a Real-world Setting W Hogan, J Li, J Shang EMNLP 2023, 16, 2023 | 3 | 2023 |
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 | 3 | 2021 |
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 |