Preprints
“Combining Evidence Across Filtrations Using Adjusters”
Y. J. Choe, A. Ramdas
Under Review, 2025+- Invited talk at ICSDS 2024; contributed talk at JSM 2024
- Links: arXiv, slides (ICSDS 2024), slides (full), code, blog
“The Geometry of Categorical and Hierarchical Concepts in LLMs”
K. Park, Y. J. Choe, Y. Jiang, V. Veitch
Under Review, 2025+
Publications
Asterisks (*) denote equal contribution.
“The Linear Representation Hypothesis and the Geometry of LLMs”
K. Park, Y. J. Choe, V. Veitch
International Conference on Machine Learning (ICML), 2024“Counterfactually Comparing Abstaining Classifiers”
Y. J. Choe, A. Gangrade, A. Ramdas
Advances in Neural Information Processing Systems (NeurIPS), 2023- Presented at INFORMS 2024 (invited session on Causal Inference; slides)
- Preliminary work presented at ICML 2023 Workshop on Counterfactuals in Minds and Machines
- Links: proceedings, arXiv, slides (full-length), poster, code, video (15-min talk)
“Comparing Sequential Forecasters”
Y. J. Choe, A. Ramdas
Operations Research, 2023“KorNLI and KorSTS: New Benchmark Datasets for Korean Natural Language Understanding”
J. Ham*, Y. J. Choe*, K. Park*, I. Choi, H. Soh
Findings of the ACL: EMNLP (EMNLP-Findings), 2020- Links: proceedings, arXiv, data
“word2word: A Collection of Bilingual Lexicons for 3,564 Language Pairs”
Y. J. Choe*, K. Park*, D. Kim*
Language Resources and Evaluation Conference (LREC), 2020- Links: proceedings, arXiv, code
“Jejueo Datasets for Machine Translation and Speech Synthesis”
K. Park, Y. J. Choe, J. Ham
Language Resources and Evaluation Conference (LREC), 2020- Links: proceedings, arXiv, code
- Links: proceedings, arXiv, code
“Predicting Drug–Target Interaction Using a Novel Graph Neural Network with 3D Structure-Embedded Graph Representation”
J. Lim, S. Ryu, K. Park, Y. J. Choe, J. Ham, W. Y. Kim
Journal of Chemical Information and Modeling, 2019“A Neural Grammatical Error Correction System Built On Better Pre-training and Sequential Transfer Learning”
Y. J. Choe*, J. Ham*, K. Park*, Y. Yoon*
Workshop on Building Educational Applications (BEA), 2019- Runner-up (Top-2 Submission), BEA Workshop Shared Task
- Links: proceedings, arXiv, code
“Discovery of Natural Language Concepts in Individual Units of CNNs”
S. Na, Y. J. Choe, D. Lee, G. Kim
International Conference on Learning Representations (ICLR), 2019- Links: proceedings, arXiv, code
“Local White Matter Architecture Defines Functional Brain Dynamics”
Y. J. Choe, S. Balakrishnan, A. Singh, J. M. Vettel, T. Verstynen
IEEE Int’l Conference on Systems, Man, and Cybernetics (IEEE SMC), 2018- Franklin V. Taylor Memorial Award (for Best Paper & Oral Presentation), IEEE SMC Society
- Links: proceedings, arXiv, slides
Ph.D. Thesis
- “Comparing Forecasters and Abstaining Classifiers”
Y. J. Choe
Ph.D. Thesis, Carnegie Mellon University, 2023
Miscellaneous Articles
“An Empirical Study of Invariant Risk Minimization”
Y. J. Choe, J. Ham, K. Park
ICML Workshop on Uncertainty and Robustness in Deep Learning, 2020“Probabilistic Interpretations of Recurrent Neural Networks”
Y. J. Choe*, J. Shin*, N. Spencer*
Technical Report, 2017“A Statistical Analysis of Neural Networks”
Y. J. Choe
Technical Report, 2016“Learning Diverse Overcomplete Dictionaries via Determinantal Priors”
M. Al-Shedivat, Y. J. Choe, N. Spencer, E. P. Xing
ICML Workshop on Geometry in Machine Learning, 2016