A power-optimized CMOS LC VCO with wide tuning range in 0.5-V supply. - Dongmin Park; SeongHwan Cho (ISCAS, 2006)

A fractional-N frequency synthesizer using high-OSR delta-sigma modulator and nested-PLL. - Pyoungwon Park; Dongmin Park; SeongHwan Cho (CICC, 2011)

A 14.2mW 2.55-to-3GHz cascaded PLL with reference injection, 800MHz delta-sigma modulator and 255fsrms integrated jitter in 0.13μm CMOS. - Dongmin Park; SeongHwan Cho (ISSCC, 2012)

A 14.2 mW 2.55-to-3 GHz Cascaded PLL With Reference Injection and 800 MHz Delta-Sigma Modulator in 0.13 μ m CMOS. - Dongmin Park; SeongHwan Cho (IEEE J. Solid State Circuits, 2012)

A 2.4 GHz Fractional-N Frequency Synthesizer With High-OSR ΔΣ Modulator and Nested PLL. - Pyoungwon Park; Dongmin Park; SeongHwan Cho (IEEE J. Solid State Circuits, 2012)

End-to-end design consideration of a radar altimeter for terrain-aided navigation. - Joohwan Chun; Sanghyouk Choi; Inchan Paek; Dongmin Park; Kyungju Yoo (SAR, 2013)

Load mapping for seamless interface between hydrodynamics and structural analyses. - Joonghyun Ji; Kangwook Kim; Minkook Seo; Taeyoung Kim; Dongmin Park; Yonghwan Kim; Kwang Hee Ko (Adv. Eng. Softw., 2014)

Adaptive beamforming for low-angle target tracking under multipath interference. - Dongmin Park; Eunjung Yang; Soyeon Ahn; Joohwan Chun (IEEE Trans. Aerosp. Electron. Syst., 2014)

Continual Learning by Asymmetric Loss Approximation With Single-Side Overestimation. - Dongmin Park; Seokil Hong; Bohyung Han; Kyoung Mu Lee (ICCV, 2019)

MLAT: Metric Learning for kNN in Streaming Time Series. - Dongmin Park; Susik Yoon; Hwanjun Song; Jae-Gil Lee 001 (CoRR, 2019)

Prestopping: How Does Early Stopping Help Generalization against Label Noise? - Hwanjun Song; Minseok Kim; Dongmin Park; Jae-Gil Lee 001 (CoRR, 2019)

Hi-COVIDNet: Deep Learning Approach to Predict Inbound COVID-19 Patients and Case Study in South Korea. - Minseok Kim; Junhyeok Kang; Doyoung Kim; Hwanjun Song; Hyangsuk Min; Youngeun Nam; Dongmin Park; Jae-Gil Lee 001 (KDD, 2020)

TRAP: Two-level Regularized Autoencoder-based Embedding for Power-law Distributed Data. - Dongmin Park; Hwanjun Song; Minseok Kim; Jae-Gil Lee 001 (WWW, 2020)

Learning from Noisy Labels with Deep Neural Networks: A Survey. - Hwanjun Song; Minseok Kim; Dongmin Park; Jae-Gil Lee 001 (CoRR, 2020)

Two-Phase Learning for Overcoming Noisy Labels. - Hwanjun Song; Minseok Kim; Dongmin Park; Jae-Gil Lee 001 (CoRR, 2020)

Robust Learning by Self-Transition for Handling Noisy Labels. - Hwanjun Song; Minseok Kim; Dongmin Park; Yooju Shin; Jae-Gil Lee 001 (KDD, 2021)

Task-Agnostic Undesirable Feature Deactivation Using Out-of-Distribution Data. - Dongmin Park; Hwanjun Song; Minseok Kim; Jae-Gil Lee 001 (NeurIPS, 2021)

Meta-Learning for Online Update of Recommender Systems. - Minseok Kim; Hwanjun Song; Yooju Shin; Dongmin Park; Kijung Shin; Jae-Gil Lee 001 (AAAI, 2022)

Multi-view POI-level Cellular Trajectory Reconstruction for Digital Contact Tracing of Infectious Diseases. - Dongmin Park; Junhyeok Kang; Hwanjun Song; Susik Yoon; Jae-Gil Lee 001 (ICDM, 2022)

Meta-Query-Net: Resolving Purity-Informativeness Dilemma in Open-set Active Learning. - Dongmin Park; Yooju Shin; Jihwan Bang; Youngjun Lee; Hwanjun Song; Jae-Gil Lee 001 (NeurIPS, 2022)

Context Consistency Regularization for Label Sparsity in Time Series. - Yooju Shin; Susik Yoon; Hwanjun Song; Dongmin Park; Byunghyun Kim; Jae-Gil Lee 001; Byung Suk Lee 001 (ICML, 2023)

Robust Data Pruning under Label Noise via Maximizing Re-labeling Accuracy. - Dongmin Park; Seola Choi; Doyoung Kim; Hwanjun Song; Jae-Gil Lee 001 (NeurIPS, 2023)

Learning From Noisy Labels With Deep Neural Networks: A Survey. - Hwanjun Song; Minseok Kim; Dongmin Park; Yooju Shin; Jae-Gil Lee 001 (IEEE Trans. Neural Networks Learn. Syst., 2023)

Adaptive Shortcut Debiasing for Online Continual Learning. - Doyoung Kim; Dongmin Park; Yooju Shin; Jihwan Bang; Hwanjun Song; Jae-Gil Lee 001 (AAAI, 2024)

One Size Fits All for Semantic Shifts: Adaptive Prompt Tuning for Continual Learning. - Doyoung Kim; Susik Yoon; Dongmin Park; Youngjun Lee; Hwanjun Song; Jihwan Bang; Jae-Gil Lee 001 (ICML, 2024)

Prioritizing Informative Features and Examples for Deep Learning from Noisy Data. - Dongmin Park (CoRR, 2024)

Mitigating Dialogue Hallucination for Large Multi-modal Models via Adversarial Instruction Tuning. - Dongmin Park; Zhaofang Qian; Guangxing Han; Ser-Nam Lim (CoRR, 2024)

Test-time Alignment of Diffusion Models without Reward Over-optimization. - Sunwoo Kim 007; Minkyu Kim; Dongmin Park (ICLR, 2025)

Rare-to-Frequent: Unlocking Compositional Generation Power of Diffusion Models on Rare Concepts with LLM Guidance. - Dongmin Park; Sebin Kim; Taehong Moon; Minkyu Kim; Kangwook Lee 001; Jaewoong Cho (ICLR, 2025)

Active Learning for Continual Learning: Keeping the Past Alive in the Present. - Jaehyun Park; Dongmin Park; Jae-Gil Lee 001 (ICLR, 2025)

Alignment without Over-optimization: Training-Free Solution for Diffusion Models. - Sunwoo Kim 007; Minkyu Kim; Dongmin Park (CoRR, 2025)

Orak: A Foundational Benchmark for Training and Evaluating LLM Agents on Diverse Video Games. - Dongmin Park; Minkyu Kim; Beongjun Choi; Junhyuck Kim; Keon Lee; Jonghyun Lee; Inkyu Park; Byeong-Uk Lee; Jaeyoung Hwang; Jaewoo Ahn; Ameya Sunil Mahabaleshwarkar; Bilal Kartal; et al. (CoRR, 2025)

Can Large Language Models Develop Strategic Reasoning? Post-training Insights from Learning Chess. - Dongyoon Hwang; Hojoon Lee; Jaegul Choo; Dongmin Park; Jongho Park (CoRR, 2025)