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Conference Proceedings & Journal Articles

• Sujeong Im*, Jungwoo Oh*, Edward Choi, 2025, LabTOP: A Unified Model for Lab Test Outcome Prediction on Electronic Health Records, Proc. of Conference on Health, Inference, and Learning (CHIL) 2025, [GitHub Repo]
• Daeun Kyung, Junu Kim, Tackeun Kim, Edward Choi, 2025, Towards Predicting Temporal Changes in a Patient's Chest X-ray Images based on Electronic Health Records, Proc. of Conference on Health, Inference, and Learning (CHIL) 2025, [GitHub Repo]
• Alban Bornet, Dimitrios Proios, Anthony Yazdani, Fernando Jaume Santero, Guy Haller, Edward Choi, Douglas Teodoro, 2025, Comparing Neural Language Models for Medical Concept Representation and Patient Trajectory Prediction, Artificial Intelligence in Medicine
• Sungjin Park, Xiao Liu, Yeyun Gong, Edward Choi, 2025, Ensembling Large Language Models with Process Reward-Guided Tree Search for Better Complex Reasoning, Proc. of North American Chapter of the Association for Computational Linguistics (NAACL) 2025
• Soyoung Yang, Hojun Cho, Jiyoung Lee, Sohee Yoon, Edward Choi, Jaegul Choo, Won Ik Cho, 2025, Single Ground Truth Is Not Enough: Add Linguistic Variability to Aspect-based Sentiment Analysis Evaluation, Proc. of North American Chapter of the Association for Computational Linguistics (NAACL) 2025
• Yeonsu Kwon*, Jiho Kim*, Gyubok Lee, Seongsu Bae, Daeun Kyung, Wonchul Cha, Tom Pollard, Alistair Johnson, Edward Choi, 2024, EHRCon: Dataset for Checking Consistency between Unstructured Notes and Structured Tables in Electronic Health Records, Proc. of Neural Information Processing Systems (NeurIPS) 2024 Datasets and Benchmarks (Spotlight), [GitHub Repo]
• Sunjun Kweon*, Jiyoun Kim*, Heeyoung Kwak, Dongchul Cha, Hangyul Yoon, Kwanghyun Kim, Seunghyun Won, Edward Choi, 2024, EHRNoteQA: A Patient-Specific Question Answering Benchmark for Evaluating Large Language Models in Clinical Settings, Proc. of Neural Information Processing Systems (NeurIPS) 2024 Datasets and Benchmarks, [GitHub Repo]
• Junhyuk Seo*, Dasol Choi*, Won Chul Cha, Minha Kim, Haanju Yoo, Namkee Oh, YongJin Yi, Kye Hwa Lee, Edward Choi, Taerim Kim, 2024, Evaluation Framework of Large Language Models in Medical Documentation: Development and Usability Study, Journal of Medical Internet Research (JMIR)
• Daehoon Gwak*, Junwoo Park*, Minho Park, Chaehun Park, Hyunchan Lee, Edward Choi, Jaegul Choo, 2024, Forecasting Future International Events: A Reliable Dataset for Text-Based Event Modeling, Findings in Empirical Methods in Natural Language Processing (EMNLP) 2024
• Jongseong Jang*, Daeun Kyung*, Seung Hwan Kim, Honglak Lee, Kyunghoon Bae, Edward Choi, 2024, Significantly Improving Zero-shot X-ray Pathology Classification via Fine-tuning Pre-trained Image-Text Encoders, Scientific Reports
• Hyunseung Chung, Sumin Jo, Yeonsu Kwon, Edward Choi, 2024, Time is Not Enough: Time-Frequency based Explanation for Time-Series Black-Box Models, Proc. of International Conference on Information and Knowledge Management (CIKM) 2024, [GitHub Repo]
• Junu Kim, Chaeeun Shim, Bosco Seong Kyu Yang, Chami Im, Sung Yoon Lim, Han-Gil Jeong, Edward Choi, 2024, General-Purpose Retrieval-Enhanced Medical Prediction Model Using Near-Infinite History, Proc. of Machine Learning for Healthcare (MLHC) 2024, [GitHub Repo]
• Jiyoung Lee*, Minwoo Kim*, Seungho Kim, Junghwan Kim, Seunghyun Won, Hwaran Lee, Edward Choi, 2024, KorNAT: LLM Alignment Benchmark for Korean Social Values and Common Knowledge, Findings in Association for Computational Linguistics (ACL) 2024, [Official Webpage]
• Sunjun Kweon*, Junu Kim*, Jiyoun Kim, Sujeong Im, Eunbyeol Cho, Seongsu Bae, Jungwoo Oh, Gyubok Lee, Jong Hak Moon, Seng Chan You, Seungjin Baek, Chang Hoon Han, Yoon Bin Jung, Yohan Jo, Edward Choi, 2024, Publicly Shareable Clinical Large Language Model Built on Synthetic Clinical Notes, Findings in Association for Computational Linguistics (ACL) 2024, [7B Model Repo], [13B Model Repo]
• Jaehee Ryu*, Seonhee Cho*, Gyubok Lee, Edward Choi, 2024, EHR-SeqSQL: A Sequential Text-to-SQL Dataset For Interactively Exploring Electronic Health Records, Findings in Association for Computational Linguistics (ACL) 2024, [GitHub Repo]
• Hyungyung Lee, Da Young Lee, Wonjae Kim, Jin-Hwa Kim, Tackeun Kim, Jihang Kim, Leonard Sunwoo, Edward Choi, 2024, Vision-Language Generative Model for View-Specific Chest X-ray Generation, Proc. of Conference on Health, Inference, and Learning (CHIL) 2024, [GitHub Repo]
• Junwoo Park, Daehoon Gwak, Jaegul Choo, Edward Choi, 2024, Self-Supervised Contrastive Learning for Long-term Forecasting, Proc. of International Conference on Learning Representations (ICLR) 2024, [GitHub Repo]
• Sungjin Park, Edward Choi, 2024, Multimodal Transformer with a Low-Computational-Cost Guarantee, Proc. of International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2024
• Kiduk Kim, Kyungjin Cho, Ryoungwoo Jang, Sunggu Kyung, Soyoung Lee, Sungwon Ham, Edward Choi, Gil-Sun Hong, Namkug Kim, 2024, Updated Primer on Generative Artificial Intelligence and Large Language Models in Medical Imaging for Medical Professionals, Korean Journal of Radiology (KJR)
• Kyunghoon Hur, Jungwoo Oh, Junu Kim, Min Jae Lee, Eunbyeol Cho, Jiyoun Kim, Seong-Eun Moon, Young-Hak Kim, Louis Atallah, Edward Choi, 2024, GenHPF : General Healthcare Predictive Framework for Multi-task Multi-source Learning, Journal of Biomedical and Health Informatics (JBHI), [GitHub Repo]
• Jiho Kim, Yeonsu Kwon, Yohan Jo, Edward Choi, 2023, KG-GPT: A General Framework for Reasoning on Knowledge Graphs Using Large Language Models, Findings in Empirical Methods in Natural Language Processing (EMNLP) 2023, [GitHub Repo]
• Seongsu Bae*, Daeun Kyung*, Jaehee Ryu, Eunbyeol Cho, Gyubok Lee, Sunjun Kweon, Jungwoo Oh, Lei Ji, Eric I-Chao Chang, Tackeun Kim, Edward Choi, 2023, EHRXQA: A Multi-Modal Question Answering Dataset for Electronic Health Records with Chest X-ray Images, Proc. of Neural Information Processing Systems (NeurIPS) 2023 Datasets and Benchmarks, [GitHub Repo]
• Jiyoung Lee, Seungho Kim, Seunghyun Won, Joonseok Lee, Marzyeh Ghassemi, James Thorne, Jaeseok Choi, O-Kil Kwon, Edward Choi, 2023, VisAlign: Dataset for Measuring the Alignment between AI and Humans in Visual Perception, Proc. of Neural Information Processing Systems (NeurIPS) 2023 Datasets and Benchmarks, [GitHub Repo]
• Jungwoo Oh, Seongsu Bae, Gyubok Lee, Joon-myoung Kwon, Edward Choi, 2023, ECG-QA: A Comprehensive Question Answering Dataset Combined With Electrocardiogram, Proc. of Neural Information Processing Systems (NeurIPS) 2023 Datasets and Benchmarks, [GitHub Repo]
• Kwanhyung Lee, Soojeong Lee, Sangchul Hahn, Heejung Hyun, Edward Choi, Byungeun Ahn, Joohyung Lee, 2023, Learning Missing Modal Electronic Health Records with Unified Multi-modal Data Embedding and Modality-Aware Attention, Proc. of Machine Learning for Healthcare (MLHC) 2023 (Oral Spotlight)
• Junwoo Park, Jungsoo Lee, Youngin Cho, Woncheol Shin, Dongmin Kim, Jaegul Choo, Edward Choi, 2023, Deep Imbalanced Time-series Forecasting via Local Discrepancy Density, Proc. of European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases (ECML-PKDD) 2023
• Jiho Kim, Sungjin Park, Yeonsu Kwon, Yohan Jo, James Thorne, Edward Choi, 2023, FactKG: Fact Verification via Reasoning on Knowledge Graph, Proc. of Association for Computational Linguistics (ACL) 2023, [GitHub Repo]
• Sunjun Kweon, Yeonsu Kwon, Seonhee Cho, Yohan Jo, Edward Choi, 2023, Open-WikiTable : Dataset for Open Domain Question Answering with Complex Reasoning over Table, Findings in Association for Computational Linguistics (ACL) 2023, [GitHub Repo]
• Eunbyeol Cho*, Min Jae Lee*, Kyunghoon Hur, Jiyoun Kim, Jinsung Yoon, Edward Choi, 2023, Rediscovery of CNN's Versatility for Text-based Encoding of Raw Electronic Health Records, Proc. of Conference on Health, Inference, and Learning (CHIL) 2023 (Oral Presentation)
• Seongjun Yang*, Hyeonji Hwang*, Daeyoung Kim, Radhika Dua, Jong-Yeup Kim, Eunho Yang, Edward Choi, 2023, Towards the Practical Utility of Federated Learning in the Medical Domain, Proc. of Conference on Health, Inference, and Learning (CHIL) 2023, [GitHub Repo]
• Hyunseung Chung, Jiho Kim, Joon-myoung Kwon, Ki-Hyun Jeon, Min Sung Lee, Edward Choi, 2023, Text-To-ECG: 12-Lead Electrocardiogram Synthesis Conditioned on Clinical Text Reports, Proc. of International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2023
• Daeun Kyung*, Kyungmin Jo*, Jaegul Choo, Joonseok Lee, Edward Choi, 2023, Perspective Projection-Based 3D CT Reconstruction from Biplanar X-rays, Proc. of International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2023 (Oral Presentation, Best Student Paper Award), [GitHub Repo]
• Woncheol Shin, Gyubok Lee, Jiyoung Lee, Eunyi Lyou, Joonseok Lee, Edward Choi, 2023, Exploration into Translation-Equivariant Image Quantization, Proc. of International Conference on Acoustics, Speech, and Signal Processing (ICASSP) 2023 (Oral Presentation, Top 3% Paper Recognition), [GitHub Repo]
• Jungsoo Lee, Jeonghoon Park, Daeyoung Kim, Juyoung Lee, Edward Choi, Jaegul Choo, 2023, Revisiting the Importance of Amplifying Bias for Debiasing, Proc. of Association for the Advancement of Artificial Intelligence (AAAI) 2023 (Oral Presentation), [GitHub Repo]
• Radhika Dua, Seongjun Yang, Yixuan Li, Edward Choi, 2023, Task Agnostic and Post-hoc Unseen Distribution Detection, Proc. of Winter Conference on Applications of Computer Vision (WACV) 2023
• Sungjin Park, Seungwoo Ryu, Edward Choi, 2022, Do Language Models Understand Measurements?, Findings in Empirical Methods in Natural Language Processing (EMNLP) 2022
• Jiyoung Lee, Hantae Kim, Hyunchang Cho, Edward Choi, Cheonbok Park, 2022, Specializing Multi-domain NMT via Penalizing Low Mutual Information, Proc. of Empirical Methods in Natural Language Processing (EMNLP) 2022
• Hojun Cho, Dohee Kim, Seungwoo Ryu, ChaeHun Park, Hyungjong Noh, Jeong-in Hwang, Minseok Choi, Edward Choi, Jaegul Choo, 2022, Rethinking Style Transformer with Energy-based Interpretation: Adversarial Unsupervised Style Transfer using a Pretrained Model, Proc. of Empirical Methods in Natural Language Processing (EMNLP) 2022
• Gyubok Lee, Hyeonji Hwang, Seongsu Bae, Yeonsu Kwon, Woncheol Shin, Seongjun Yang, Minjoon Seo, Jong-Yeup Kim, Edward Choi, 2022, EHRSQL: A Practical Text-to-SQL Benchmark for Electronic Health Records, Proc. of Neural Information Processing Systems (NeurIPS) 2022 Datasets and Benchmarks, [GitHub Repo]
• Hyungyung Lee, Sungjin Park, Joonseok Lee, Edward Choi, 2022, Unconditional Image-Text Pair Generation with Multimodal Cross Quantizer, Proc. of British Machine Vision Conference (BMVC) 2022, [GitHub Repo]
• Jong Hak Moon, Wonjae Kim, Edward Choi, 2022, Correlation between Alignment-Uniformity and Performance of Dense Contrastive Representations, Proc. of British Machine Vision Conference (BMVC) 2022
• Jong Hak Moon*, Hyungyung Lee*, Woncheol Shin, Young-Hak Kim, Edward Choi, 2022, Multi-modal Understanding and Generation for Medical Images and Text via Vision-Language Pre-Training, Journal of Biomedical and Health Informatics (JBHI), [GitHub Repo]
• Taehee Kim*, ChaeHun Park*, Jimin Hong, Radhika Dua, Edward Choi, Jaegul Choo, 2022, Reweighting Strategy based on Synthetic Data Identification for Sentence Similarity, Proc. of International Conference on Computational Linguistics (COLING) 2022
• Kwanhyung Lee*, Hyewon Jeong*, Seyun Kim, Donghwa Yang, Hoon-Chul Kang, Edward Choi, 2022, Real-Time Seizure Detection using EEG: A Comprehensive Comparison of Recent Approaches under a Realistic Setting, Proc. of Conference on Health, Inference, and Learning (CHIL) 2022, [GitHub Repo]
• Jungwoo Oh, Hyunseung Chung, Joon-myoung Kwon, Dong-gyun Hong, Edward Choi, 2022, Lead-agnostic Self-supervised Learning for Local and Global Representations of Electrocardiogram, Proc. of Conference on Health, Inference, and Learning (CHIL) 2022, [GitHub Repo]
• Daeyoung Kim, Seongsu Bae, Seungho Kim, Edward Choi, 2022, Uncertainty-Aware Text-to-Program for Question Answering on Structured Electronic Health Records, Proc. of Conference on Health, Inference, and Learning (CHIL) 2022, [GitHub Repo]
• Sungjin Park, Seongsu Bae, Jiho Kim, Tackeun Kim, Edward Choi, 2022, Graph-Text Multi-Modal Pre-training for Medical Representation Learning, Proc. of Conference on Health, Inference, and Learning (CHIL) 2022, [GitHub Repo]
• Kyunghoon Hur*, Jiyoung Lee*, Jungwoo Oh, Wesley Price, Young-Hak Kim, Edward Choi, 2022, Unifying Heterogenous Electronic Health Records Systems via Text-Based Code Embedding, Proc. of Conference on Health, Inference, and Learning (CHIL) 2022, , [GitHub Repo]
• Chayakrit Krittanawong, Kipp W. Johnson, Edward Choi, Scott Kaplin, Eric Venner, Mullai Murugan, Zhen Wang, Benjamin S. Glicksberg, Christopher I. Amos, Michael C. Schatz, W. H. Wilson Tang, 2022, Artificial Intelligence and Cardiovascular Genetics, Life, doi:10.3390/life12020279.
• Seongsu Bae, Daeyoung Kim, Jiho Kim, Edward Choi, 2021, Question Answering for Complex Electronic Health Records Database using Unified Encoder-Decoder Architecture, Proc. of Machine Learning for Health (ML4H) 2021 (Oral Spotlight, Best Poster Award)
• Kangyeol Kim*, Sunghyun Park*, Junsoo Lee, Joonseok Lee, Sookyung Kim, Jaegul Choo, Edward Choi, 2021, Continuous-Time Video Generation via Learning Motion Dynamics with Neural ODE, Proc. of British Machine Vision Conference (BMVC) 2021
• Junwoo Park, Youngwoo Cho, Haneol Lee, Jaegul Choo, Edward Choi, 2021, Knowledge Graph-based Question Answering with Electronic Health Records, Proc. of Machine Learning for Healthcare (MLHC) 2021, [GitHub Repo]
• Gyubok Lee*, Seongjun Yang*, Edward Choi, 2021, Improving Lexically Constrained Neural Machine Translation with Source-Conditioned Masked Span Prediction, Proc. of Association of Computational Linguistics (ACL) 2021, [GitHub Repo]
• Sunghyun Park*, Kangyeol Kim*, Junsoo Lee, Jaegul Choo, Joonseok Lee, Sookyung Kim, Edward Choi, 2021, Vid-ODE: Continuous-Time Video Generation with Neural Ordinary Differential Equation, Proc. of Association for the Advancement of Artificial Intelligence (AAAI) 2021, [GitHub Repo]
• Michael W. Dusenberry, Dustin Tran, Edward Choi, Jonas Kemp, Jeremy Nixon, Ghassen Jerfel, Katherine Heller, Andrew M. Dai, 2020, Analyzing the Role of Model Uncertainty for Electronic Health Records, Proc. of Conference on Health, Inference, and Learning (CHIL) 2020
• Edward Choi, Zhen Xu, Yujia Li, Michael W. Dusenberry, Gerardo Flores, Yuan Xue, Andrew M. Dai, 2020, Learning the Graphical Structure of Electronic Health Records using Graph Convolutional Transformer, Proc. of Association for the Advancement of Artificial Intelligence (AAAI) 2020, [GitHub Repo]
• Chayakrit Krittanawong, Albert J. Rogers, Mehmet Aydar, Edward Choi, Kipp W. Johnson, Zhen Wang,Sanjiv M. Narayan, 2019, Integrating Blockchain Technology with Artificial Intelligence for Cardiovascular Medicine, Nature Reviews Cardiology, doi:10.1038/s41569-019-0294-y.
• Edward Choi, Cao Xiao, Walter F. Stewart, Jimeng Sun, 2018, MiME: Multilevel Medical Embedding of Electronic Health Records for Predictive Healthcare, Proc. of Neural Information Processing Systems (NIPS) 2018, [GitHub Repo]
• Bum Chul Kwon, Min-Je Choi, Joanne Taery Kim, Edward Choi, Young Bin Kim, Soonwook Kwon, Jimeng Sun, Jaegul Choo, 2018, RetainVis: Visual Analytics with Interpretable and Interactive Recurrent Neural Networks on Electronic Medical Records, Proc. of IEEE VIS 2018.
• Cao Xiao, Edward Choi, Jimeng Sun, 2018, Opportunities and Challenges in Developing Deep Learning Models using Electronic Health Records Data: A Systematic Review, Journal of the American Medical Informatics Association (JAMIA), doi:10.1093/jamia/ocy068.
• Ariel Gordon, Elad Eban, Ofir Nachum, Bo Chen, Hao Wu, Tien-Ju Yang, Edward Choi, 2018, MorphNet: Fast & Simple Resource-Constrained Structure Learning of Deep Networks, Proc. of Conference on Computer Vision and Pattern Recognition (CVPR) 2018.
• Edward Choi, Angeliki Lazaridou, Nando de Freitas, 2018, Compositional Obverter Communication Learning from Raw Visual Input, Proc. of International Conference on Learning Representations (ICLR) 2018., Implementation by Ben Bogin
• Edward Choi, Siddharth Biswal, Bradley Malin, Jon Duke, Walter F. Stewart, Jimeng Sun, 2017, Generating Multi-label Discrete Patient Records using Generative Adversarial Networks, Proc. of Machine Learning for Healthcare (MLHC) 2017, [GitHub Repo]
• Edward Choi, Mohammad Taha Bahadori, Le Song, Walter F. Stewart, Jimeng Sun, 2017, GRAM: Graph-based Attention Model for Healthcare Representation Learning, Proc. of Knowledge Discovery and Data Mining (KDD) 2017, [GitHub Repo]
• Edward Choi, Mohammad Taha Bahadori, Joshua A. Kulas, Andy Schuetz, Walter F. Stewart, Jimeng Sun, 2016, RETAIN: An Interpretable Predictive Model for Healthcare using Reverse Time Attention Mechanism, In Proc. of Neural Information Processing Systems (NIPS) 2016, pp.3504-3512. [GitHub Repo], TensorFlow Implementation by Optum
• Edward Choi, Mohammad Taha Bahadori, Elizabeth Searles, Catherine Coffey, Michael Thompson, James Bost, Javier Tejedor-Sojo, Jimeng Sun, 2016, Multi-layer Representation Learning for Medical Concepts, In Proc. of Knowledge Discovery and Data Mining (KDD) 2016, pp.1495-1504. [GitHub Repo]
• Edward Choi, Mohammad Taha Bahadori, Andy Schuetz, Walter F. Stewart, Jimeng Sun, 2016, Doctor AI: Predicting Clinical Events via Recurrent Neural Networks, In Proc. of Machine Learning for Healthcare (MLHC) 2016, pp.301-318. [GitHub Repo]
• Edward Choi, Andy Schuetz, Walter F. Stewart, Jimeng Sun, 2016, Using Recurrent Neural Network Models for Early Detection of Heart Failure Onset, Journal of the American Medical Informatics Association (JAMIA), doi:10.1093/jamia/ocw112. [GitHub Repo]
• Edward Choi, Nan Du, Robert Chen, Le Song, Jimeng Sun, 2015, Constructing Disease Network and Temporal Progression Model via Context-Sensitive Hawkes Process, In Proc. of International Conference of Data Mining (ICDM) 2015, pp.721-726, Full version (A kinder random process intro, scalability experiments)
• Edward Choi, Jina Dcruz, Sizhe Lin, Kelly Ryder, Aashu Singh, Hang Su, I-SMILE: similarity based just-in-time recommendation system for public health, American Medical Informatics Association (AMIA) 2015, poster presentation as a top-7 finalist in Student Design Challenge
• Edward Choi, Jina Dcruz, Sizhe Lin, Aashu Singh, Hang Su, Kelly Ryder, Sridhar R. Papagari Sangareddy, Herman Tolentino, Jimeng Sun, 2015, System architecture of CDC I-SMILE recommendation engine, American Medical Informatics Association (AMIA) 2015, poster presentation
• Edward Choi, Hyunki Kim, Changki Lee, 2014. Balanced Korean word spacing with structural SVM, In Proc. of Empirical Methods in Natural Language Processing (EMNLP) 2014, pp.875-879.
• Jeong Heo, Pum-Mo Ryu, Yoonjae Choi, Hyunki Kim, Cheol Young Ock, 2013, An issue event search system based on big data for decision supporting: Social Wisdom, Journal of Korean Institute of Information Scientists and Engineers (KIISE): Software and Applications, vol.40, no.7, pp.381-394.
• Yoonjae Choi, Pum-Mo Ryu, Hyunki Kim, Changki Lee, 2013. Extracting events from web documents for social media monitoring using structured SVM, The Institute of Electronics, Information and Communication Engineers(IEICE) Transactions on Information and Systems, vol.E96-D, no.6, pp.1410-1414.
• Jeong Heo, Pum-Mo Ryu, Yoonjae Choi, Hyunki Kim, 2012, Event template extraction for the decision support based on social media, In Proc. of The 24th Annual Conference on Human & Cognitive Language Technology (HCLT) 2012, pp.53-57. (Best paper)
• Yoonjae Choi, Jong C. Park, 2009, Extracting melodies from piano solo music based on its characteristics, Journal of Korean Institute of Information Scientists and Engineers (KIISE): Computing Practices and Letters, vol.15, no.12, pp.923-927.
• Yoonjae Choi, Jong C. Park, 2009, Extracting melodies from piano solo music based on characteristics of music, In Proc. of Korea Computer Congress (KCC) 2009, pp.124-125. (Best paper)
• Yoonjae Choi, Hodong Lee, Ho-Joon Lee, Jong C. Park, 2009, Extracting melodies from polyphonic piano solo music based on patterns of music structure, In Proc. of Human Computer Interaction (HCI) Korea 2009, pp.725-732.

Workshops & Preprints

• Sumin Jo*, Junseong Choi*, Jiho Kim, Edward Choi, 2025, R2-KG: General-Purpose Dual-Agent Framework for Reliable Reasoning on Knowledge Graphs, arXiv:2502.12767
• Jiho Kim, Woosog Chay, Hyeonji Hwang, Daeun Kyung, Hyunseung Chung, Eunbyeol Cho, Yohan Jo, Edward Choi, 2024, DialSim: A Real-Time Simulator for Evaluating Long-Term Dialogue Understanding of Conversational Agents, arXiv:2406.13144, [GitHub Repo]
• Gyubok Lee, Woosog Chay, Seonhee Cho, Edward Choi, 2024, TrustSQL: Benchmarking Text-to-SQL Reliability with Penalty-Based Scoring, arXiv:2403.15879, [GitHub Repo]
• Sunjun Kweon, Byungjin Choi, Minkyu Kim, Rae Woong Park, Edward Choi, 2024, KorMedMCQA: Multi-Choice Question Answering Benchmark for Korean Healthcare Professional Licensing Examinations, arXiv:2403.01469, [HuggingFace Repo]
• Kwanhyung Lee, John Won, Heejung Hyun, Sangchul Hahn, Edward Choi, Joohyung Lee, 2023, Self-Supervised Predictive Coding with Multimodal Fusion for Patient Deterioration Prediction in Fine-grained Time Resolution, In Trustworthy Machine Learning for Healthcare Workshop at ICLR 2023
• Junu Kim, Kyunghoon Hur, Seongjun Yang, Edward Choi, 2022, Universal EHR Federated Learning Framework, In Extended abstract in Machine Learning for Health (ML4H) 2022
• Radhika Dua, Jiyoung Lee, Joon-myoung Kwon, Edward Choi, 2022, Automatic Detection of Noisy Electrocardiogram Signals without Explicit Noise Labels, In Pattern Recognition for Healthcare Analytics Workshop at ICPR 2022
• Jiyoung Lee, Wonjae Kim, Daehoon Gwak, Edward Choi, 2021, Conditional Generation of Periodic Signals with Fourier-Based Decoder, In Deep Generative Models and Downstream Applications Workshop at NeurIPS 2021
• Jeonghoon Park*, Jimin Hong*, Radhika Dua*, Daehoon Gwak, Yixuan Li, Jaegul Choo, Edward Choi, 2021, Natural Attribute-based Shift Detection, arXiv:2110.09276
• Jeonghoon Park*, Kyungmin Jo*, Daehoon Gwak*, Jimin Hong, Jaegul Choo, Edward Choi, 2020, Evaluation of Out-of-Distribution Detection Performance of Self-Supervised Learning in a Controllable Environment, In Self-Supervised Learning - Theory and Practice Workshop at NeurIPS 2020
• Daehoon Gwak, Gyuhyeon Sim, Michael Poli, Stefano Massaroli, Jaegul Choo, Edward Choi, 2020, Neural Ordinary Differential Equations for Intervention Modeling, arXiv:2010.08304.
• Sarah Wiegreffe, Edward Choi, Sherry Yan, Jimeng Sun, Jacob Eisenstein, 2019, Clinical Concept Extraction for Document-Level Coding, In Biomedical NLP Workshop at ACL 2019
• Mohammad Taha Bahadori, Krzysztof Chalupka, Edward Choi, Robert Chen, Walter F. Stewart, Jimeng Sun, 2017, Causal Regularization, arXiv:1702.02604.
• Edward Choi, Andy Schuetz, Walter F. Stewart, Jimeng Sun, 2016, Medical Concept Representation Learning from Electronic Health Records and its Application on Heart Failure Prediction, arXiv:1602.03686.