Kyunghyun Cho
Glen de Vries Chaired Professor of Computer Science and Data Science
Works on deep learning for natural language, including neural machine translation, language models and machine learning for scientific discovery.
Kyunghyun Cho's lab at NYU works on large language models and multilingual, translation & linguistics. 76 papers since 2023, 43 at top venues, mostly NeurIPS and ICLR. 10 PhD students. 100 alumni, most often to Amazon and Meta. Applications close .
At a glance
- papers, 2023–2026
- 20/ year
- at T1 venues
- 57%
- PhD students
- 10
- MS students
- 0
- alumni listed
- 100
Papers by yearfrom DBLP, 2023–2026
- 7 papers2026 · T1 3 · collecting
- 28 papers2025 · T1 15
- 24 papers2024 · T1 15
- 17 papers2023 · T1 10
T1 venuesOtherVenues: NeurIPS, ICLR, ICML, ACL, EACL
Research focuspaper titles that use each topic's words
- Large language models23 papers
- Multilingual, translation & linguistics1 paper
- machine translation1 paper
- translation1 paper
- scientific discovery0 papers
Paper list
From DBLP.
20267 papers
- ICLR (T1)Forget Forgetting: Continual Learning in a World of Abundant Memory (opens in a new tab)
- Trans. Mach. Learn. Res.MIST: Mutual Information Estimation via Supervised Training (opens in a new tab)
- ICLR (T1)Multi-modal Data Spectrum: Multi-modal Datasets are Multi-dimensional (opens in a new tab)
- LRECOpen Korean Historical Corpus: A Millennia-Scale Diachronic Collection of Public Domain Texts (opens in a new tab)
- Nat. Comput. Sci.Self-rankings as a predictor of scientific impact beyond peer review (opens in a new tab)
- ICLR (T1)Temporal Generalization: A Reality Check (opens in a new tab)
- Virtual Real.The role of design personalization in enhancing knowledge workers' experience in virtual reality workspaces (opens in a new tab)
202528 papers
- Signal Image Video Process.A Progressive risk formulation for enhanced deep learning based total knee replacement prediction in knee osteoarthritis (opens in a new tab)
- ICLR (T1)Aioli: A Unified Optimization Framework for Language Model Data Mixing (opens in a new tab)
- NeurIPS (T1)AION-1: Omnimodal Foundation Model for Astronomical Sciences (opens in a new tab)
- ICLR (T1)Concept Bottleneck Language Models For Protein Design (opens in a new tab)
- Trans. Mach. Learn. Res.Deep Autoregressive Models as Causal Inference Engines (opens in a new tab)
- NeurIPS (T1)Efficient semantic uncertainty quantification in language models via diversity-steered sampling (opens in a new tab)
- Comput. Biol. MedicineEstimation of time-to-total knee replacement surgery with multimodal modeling and artificial intelligence (opens in a new tab)
- EMNLP (T1)Following Length Constraints in Instructions (opens in a new tab)
- ICML (T1)Generalists vs. Specialists: Evaluating LLMs on Highly-Constrained Biophysical Sequence Optimization Tasks (opens in a new tab)
- NeurIPS (T1)Generative property enhancer: implicit guided generation through conditional density estimation (opens in a new tab)
- Trans. Mach. Learn. Res.Hyperparameters in Continual Learning: A Reality Check (opens in a new tab)
- EMNLP (T1)Language Models as Causal Effect Generators (opens in a new tab)
202424 papers
- IEEE Trans. Vis. Comput. Graph.: Visualization of AI-Assisted Task Guidance in AR (opens in a new tab)
- Trans. Mach. Learn. Res.Blind Biological Sequence Denoising with Self-Supervised Set Learning (opens in a new tab)
- ICML (T1)BOtied: Multi-objective Bayesian optimization with tied multivariate ranks (opens in a new tab)
- ICLR (T1)Concept Bottleneck Generative Models (opens in a new tab)
- NAACL (T1)First Tragedy, then Parse: History Repeats Itself in the New Era of Large Language Models (opens in a new tab)
- ML4H@NeurIPSHIST-AID: Leveraging Historical Patient Reports for Enhanced Multi-Modal Automatic Diagnosis (opens in a new tab)
- AHsHolistic Patient Assessment System using Digital Twin for XR Medical Teleconsultation (opens in a new tab)
- IACR Cryptol. ePrint Arch.How To Think About End-To-End Encryption and AI: Training, Processing, Disclosure, and Consent (opens in a new tab)
- NeurIPS (T1)Implicitly Guided Design with PropEn: Match your Data to Follow the Gradient (opens in a new tab)
- NeurIPS (T1)Iterative Reasoning Preference Optimization (opens in a new tab)
- NeurIPS (T1)Jointly Modeling Inter- & Intra-Modality Dependencies for Multi-modal Learning (opens in a new tab)
- Trans. Mach. Learn. Res.Learning from Natural Language Feedback (opens in a new tab)
202317 papers
- ICASSP (T1)A Comparison of Semi-Supervised Learning Techniques for Streaming ASR at Scale (opens in a new tab)
- ICLR (T1)A Non-monotonic Self-terminating Language Model (opens in a new tab)
- AsiaCCSA Transformer-based Function Symbol Name Inference Model from an Assembly Language for Binary Reversing (opens in a new tab)
- NeurIPS (T1)AbDiffuser: full-atom generation of in-vitro functioning antibodies (opens in a new tab)
- Trans. Mach. Learn. Res.Detecting incidental correlation in multimodal learning via latent variable modeling (opens in a new tab)
- Nat.Health system-scale language models are all-purpose prediction engines (opens in a new tab)
- Interspeech (T1)Improving Joint Speech-Text Representations Without Alignment (opens in a new tab)
- ACL (T1)Intriguing Effect of the Correlation Prior on ICD-9 Code Assignment (opens in a new tab)
- Trans. Mach. Learn. Res.Latent State Models of Training Dynamics (opens in a new tab)
- CLeaRLearning Causal Representations of Single Cells via Sparse Mechanism Shift Modeling (opens in a new tab)
- ICLR (T1)Linear Connectivity Reveals Generalization Strategies (opens in a new tab)
- ACL (T1)Making the Most Out of the Limited Context Length: Predictive Power Varies with Clinical Note Type and Note Section (opens in a new tab)
Where alumni went100 listed, 68% to industry
Industry 21Academia 10
Most often to
- Amazon
- Meta
Also to
- NYU
- Carnegie Mellon University
- Flatiron Institute
Apply to NYUFall 2027
Computer Science PhD (Courant / Tandon)
- Round
- Single round (December)
- Opens
- —
- GRE
- See program page
- English
- See program page
- Fee
- See program page
Not yet confirmed for this intake.
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