7 citations · 7 across the 7 of their papers we have counts for
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cs.CL2024
Learning from Negative Samples in Biomedical Generative Entity Linking
Chanhwi Kim, Hyunjae Kim, Sihyeon Park +3
Generative models have become widely used in biomedical entity linking (BioEL) due to their excellent performance and efficient memory usage. However, these models are usually trai…
cs.CL2024★ 7 cited
Augmenting Biomedical Named Entity Recognition with General-domain Resources
Yu Yin, Hyunjae Kim, Xiao Xiao +6
Training a neural network-based biomedical named entity recognition (BioNER) model usually requires extensive and costly human annotations. While several studies have employed mult…
cs.CV2024
Fine-tuning CLIP Text Encoders with Two-step Paraphrasing
Hyunjae Kim, Seunghyun Yoon, Trung Bui +4
Contrastive language-image pre-training (CLIP) models have demonstrated considerable success across various vision-language tasks, such as text-to-image retrieval, where the model…