Papers

Preprints

• “Combining Evidence Across Filtrations Using Adjusters”
  Y. J. Choe, A. Ramdas
  Under Review, 2024
  

  • 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, 2024
  

  • Best Paper Award, ICML 2024 Workshop on Mechanistic Interpretability
  • Links: arXiv, slides, poster, code

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
  

  • Preliminary work presented at NeurIPS 2023 Workshop on Causal Representation Learning
  • Links: arXiv, slides, poster, code

• “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
  

  • Poster Award (Runner-up w/ $10K Research Grant), Citadel Securities Inaugural PhD Summit
  • Preliminary work presented at 2022 Workshop on Game-Theoretic Statistics & Safe, Anytime-Valid Inference (SAVI)
    
  • Links: journal, arXiv, slides, poster, code

• “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
    

• “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

  • Links: journal, arXiv

• “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
  (Peer-reviewed & published in official proceedings. Publisher: ACL.)

  • 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
  • Links: kilthub, slides

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

  • Links: arXiv, code, slides

• “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