Gyubok Lee
According to our database1,
Gyubok Lee
authored at least 15 papers
between 2019 and 2024.
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Bibliography
2024
EHRCon: Dataset for Checking Consistency between Unstructured Notes and Structured Tables in Electronic Health Records.
CoRR, 2024
CoRR, 2024
TrustSQL: A Reliability Benchmark for Text-to-SQL Models with Diverse Unanswerable Questions.
CoRR, 2024
EHR-SeqSQL : A Sequential Text-to-SQL Dataset For Interactively Exploring Electronic Health Records.
Proceedings of the Findings of the Association for Computational Linguistics, 2024
Proceedings of the Findings of the Association for Computational Linguistics, 2024
Overview of the EHRSQL 2024 Shared Task on Reliable Text-to-SQL Modeling on Electronic Health Records.
Proceedings of the 6th Clinical Natural Language Processing Workshop, 2024
2023
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023
Proceedings of the IEEE International Conference on Acoustics, 2023
2022
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022
2021
CoRR, 2021
Erythropoiesis stimulating agent recommendation model using recurrent neural networks for patient with kidney failure with replacement therapy.
Comput. Biol. Medicine, 2021
Improving Lexically Constrained Neural Machine Translation with Source-Conditioned Masked Span Prediction.
Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021
2020
Diverse and Admissible Trajectory Forecasting Through Multimodal Context Understanding.
Proceedings of the Computer Vision - ECCV 2020, 2020
2019
Unsupervised learning approach for network intrusion detection system using autoencoders.
J. Supercomput., 2019