Ph. D. Student Researcher @ Google Research Prev: Qualcomm, DynamoFL (YCW22) Located in Seoul, South KoreaEducation
Ph.D. in Graduate School of AI (KAIST) M.S. in Data Science (KAIST) B.S. in Mathematical Science [Minor-Intellectual Property] (KAIST)I am a Ph.D. Student in Optimization & Statistical Inference (OSI) Lab @ KAIST, advised by Prof. Se-Young Yun. I worked as a PhD student researcher @ Google Research, Qualcomm AI, and DynamoFL (YCW22 Startup). My expected graduation date is Aug. 2024.
Contact: potter32 [at] kaist.ac.kr, kimtaehyeon610 [at] gmail.com (permanant)
Contact: potter32 [at] kaist.ac.kr, kimtaehyeon610 [at] gmail.com (permanant) About
My goal is to tackle trustworthy and real-world AI/ML challenges
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NLP: Instruction Tuning and Following, Parallel Decoding
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CV/NLP: Knowledge Distillation & Learning with Noisy Labels
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Data & System: Federated Learning & AutoML & Semi-Supervised Learning
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Efficiency: Efficient Deep Learning
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Game-Changing Research
️ News
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 GeneralizationOct. 2023
Working with Google Research NYC May. 2023
Invited to Liner Dev conferenceJan. 2023
Working with DynamoFL Research Team (YCW22-Startup) Working at/with
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Publications & Technical Reports
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Preprints (Under Review)
Distort, Distract, Decode: Instruction-Tuned Model Can Refine its Response from Noisy Instructions Taehyeon Kim*, Joonkee Kim*, Gihun Lee*, Se-Young Yun
Tackling Heterogeneous Label Noise in Federated Learning with Label-Mixture RegularizationTaehyeon Kim*, Donggyu Kim*, Se-Young Yun
Overcoming Heterogeneity in Federated Learning with Supernet Training and Parametric NormalizationTaehyeon Kim, Se-Young Yun
Leadership & Awards & Activities
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Research Projects
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Invited Talks
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Services & Others
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