| BioBERT: a pre-trained biomedical language representation model for biomedical text mining J Lee, W Yoon, S Kim, D Kim, S Kim, CH So, J Kang Bioinformatics 36 (4), 1234-1240, 2020 | 6032 | 2020 |
| Gemini: A family of highly capable multimodal models G Team, R Anil, S Borgeaud, Y Wu, JB Alayrac, J Yu, R Soricut, ... arXiv preprint arXiv:2312.11805, 2023 | 1493 | 2023 |
| Real-Time Open-Domain Question Answering with Dense-Sparse Phrase Index M Seo, J Lee, T Kwiatkowski, AP Parikh, A Farhadi, H Hajishirzi Annual Meeting of the Association for Computational Linguistics (ACL), 2019 | 181 | 2019 |
| Collabonet: collaboration of deep neural networks for biomedical named entity recognition W Yoon, CH So, J Lee, J Kang BMC bioinformatics 20 (10), 55-65, 2019 | 170 | 2019 |
| Biomedical Entity Representations with Synonym Marginalization M Sung, H Jeon, J Lee, J Kang Annual Meeting of the Association for Computational Linguistics (ACL), 2020 | 138 | 2020 |
| A Neural Named Entity Recognition and Multi-Type Normalization Tool for Biomedical Text Mining D Kim, J Lee, CH So, H Jeon, M Jeong, Y Choi, W Yoon, M Sung, J Kang IEEE Access 7, 73729-73740, 2019 | 136 | 2019 |
| Simple Entity-Centric Questions Challenge Dense Retrievers C Sciavolino, Z Zhong, J Lee, D Chen Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021 | 134 | 2021 |
| Learning Dense Representations of Phrases at Scale J Lee, M Sung, J Kang, D Chen Annual Meeting of the Association for Computational Linguistics (ACL), 2021 | 118 | 2021 |
| Ranking Paragraphs for Improving Answer Recall in Open-Domain Question Answering J Lee, S Yun, H Kim, M Ko, J Kang Conference on Empirical Methods in Natural Language Processing (EMNLP), 2018 | 111 | 2018 |
| Pre-trained Language Model for Biomedical Question Answering W Yoon, J Lee, D Kim, M Jeong, J Kang BioASQ Workshop, ECML PKDD, 2019 | 106 | 2019 |
| BERN2: an advanced neural biomedical named entity recognition and normalization tool M Sung, M Jeong, Y Choi, D Kim, J Lee, J Kang arXiv preprint arXiv:2201.02080, 2022 | 103 | 2022 |
| Can Language Models be Biomedical Knowledge Bases? M Sung, J Lee, S Yi, M Jeon, S Kim, J Kang Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021 | 97 | 2021 |
| Look at the First Sentence: Position Bias in Question Answering M Ko, J Lee, H Kim, G Kim, J Kang Conference on Empirical Methods in Natural Language Processing (EMNLP), 2020 | 75 | 2020 |
| Answering Questions on COVID-19 in Real-Time J Lee, SS Yi, M Jeong, M Sung, W Yoon, Y Choi, M Ko, J Kang NLP COVID-19 Workshop, EMNLP, 2020 | 56 | 2020 |
| Pandemics are catalysts of scientific novelty: Evidence from COVID‐19 M Liu, Y Bu, C Chen, J Xu, D Li, Y Leng, RB Freeman, ET Meyer, W Yoon, ... Journal of the Association for Information Science and Technology, 2021 | 53* | 2021 |
| ReSimNet: drug response similarity prediction using Siamese neural networks M Jeon, D Park, J Lee, H Jeon, M Ko, S Kim, Y Choi, AC Tan, J Kang Bioinformatics 35 (24), 5249-5256, 2019 | 53 | 2019 |
| Phrase Retrieval Learns Passage Retrieval, Too J Lee, A Wettig, D Chen Conference on Empirical Methods in Natural Language Processing (EMNLP), 2021 | 43 | 2021 |
| Contextualized Sparse Representations for Real-Time Open-Domain Question Answering J Lee, M Seo, H Hajishirzi, J Kang Annual Meeting of the Association for Computational Linguistics (ACL), 2020 | 42 | 2020 |
| Name Nationality Classification with Recurrent Neural Networks J Lee, H Kim, M Ko, D Choi, J Choi, J Kang International Joint Conference on Artificial Intelligence (IJCAI), 2081-2087, 2017 | 41 | 2017 |
| DeepNAP: Deep neural anomaly pre-detection in a semiconductor fab C Kim, J Lee, R Kim, Y Park, J Kang Information Sciences 457, 1-11, 2018 | 36 | 2018 |
Jaewoo Kang (강재우)Dept of Computer Science and Engineering, Korea UniversityVerified email at korea.ac.kr
