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Taehyeon Kim

 Prev: Google Research (NYC), Qualcomm AI, DynamoFL (YCW22)
 PhD Student @ KAIST AI [OSI Lab]
 Located in Seoul, South Korea
Education
 PhD in Graduate School of AI (KAIST)
 MS in Data Science (KAIST)
 BS in Mathematical Science (KAIST)
[Minor-Intellectual Property]
I am a Ph.D. Student in Optimization & Statistical Inference (OSI) Lab @ KAIST, advised by Prof. Se-Young Yun. I worked as a PhD Intern @ Google ResearchQualcomm AI, and DynamoFL (YCW22 Startup). My expected graduation date is Aug. 2024 (or Feb. 2025).  Contact: potter32 [at] kaist.ac.kr, kimtaehyeon610 [at] gmail.com (permanent)

 About

My goal is to tackle trustworthy and real-world AI/ML challenges
NLP: Instruction Tuning and Following, Parallel Decoding
CV/NLP: Knowledge Distillation & Learning with Noisy Labels
Data Heterogeneity: Federated Learning & AutoML & Semi-Supervised Learning
Efficiency: Efficient Deep Learning
Game-Changing Research

️ News

Jan. 2023
 1 Accepted @ ICLR2024 (Spotlight): Instruction Following on Large Language Model
Dec. 2023
 1 Accepted @ NeurIPS2023W: Instruction Tuning & Instruction Following
 1 Accepted @ NeurIPS2023: Semi-Supervised Federated Object Detection
 Attending NeurIPS 2023 @ NOLA, US  
 1 Accepted @ AAAI2024: Few-shot & Domain Generalization
Oct. 2023
 Working with Google Research NYC

Working at/with

Search
Name
When
Research
Advisor/Coworker
2023.01 - 2023.05
Semi-Supervised Object Detection
Federated Learning
Eric Lin
2021.06 - 2021.12
Neural Architecture Search
Knowledge Distillation
Heesoo Myeong
2017.03 - 2018.02
Trajectory Prediction
Jaegil Lee

 Publications & Technical Reports

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Conference and Journal
Author
COUNT19

Preprints (Under Review)

 Towards Fast Inference: Exploring and Improving Blockwise Parallel Drafts
Taehyeon Kim, Ananda Theertha Suresh, Kishore Papineni, Michael Riley, Sanjiv Kumar, Adrian Benton
 Non-linear Fusion in Federated Learning: A Hypernetwork Approach to Federated Domain Generalization
Marc Bartholet, Taehyeon Kim, Ami Beuret, Se-Young Yun, Joachim M. Buhmann
 Revisiting Early-Learning Regularization: When Federated Learning Meets Noisy Labels
Taehyeon Kim, Donggyu Kim, Se-Young Yun

 Leadership Awards  Activities

 Research Projects

 Invited Talks

 Services & Others

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 Others