| 2026 | DATE | Fast and Energy-Efficient Support for Low-Precision LLMs on PIM. | Byeori Kim, Sangjun Lee, Eunhyeok Park |
| 2026 | WACV | Stabilizing Direct Training of Spiking Neural Networks: Membrane Potential Initialization and Threshold-robust Surrogate Gradient. | Hyunho Kook, Byeongho Yu, Jeong Min Oh, Eunhyeok Park |
| 2026 | WACV | DreamCatcher: Efficient Multi-Concept Customization via Representation Finetuning. | Jungwon Lee, Changhun Lee, Eunhyeok Park |
| 2025 | ACL | SEAL: Scaling to Emphasize Attention for Long-Context Retrieval. | Changhun Lee, Minsang Seok, Jungyu Jin, Younghyun Cho, Eunhyeok Park |
| 2025 | CVPR | HOT: Hadamard-based Optimized Training. | Seonggon Kim, Juncheol Shin, Seung-taek Woo, Eunhyeok Park |
| 2025 | CVPR | PCM : Picard Consistency Model for Fast Parallel Sampling of Diffusion Models. | Junhyuk So, Jiwoong Shin, Chaeyeon Jang, Eunhyeok Park |
| 2025 | EMNLP | Efficient Latent Semantic Clustering for Scaling Test-Time Computation of LLMs. | Sungjae Lee, Hoyoung Kim, Jeongyeon Hwang, Eunhyeok Park, Jungseul Ok |
| 2025 | EMNLP | AMQ: Enabling AutoML for Mixed-precision Weight-Only Quantization of Large Language Models. | Sangjun Lee, Seung-taek Woo, Jungyu Jin, Changhun Lee, Eunhyeok Park |
| 2025 | EMNLP | PruneCD: Contrasting Pruned Self Model to Improve Decoding Factuality. | Byeongho Yu, Changhun Lee, Jungyu Jin, Eunhyeok Park |
| 2025 | ICCV | Grouped Speculative Decoding for Autoregressive Image Generation. | Junhyuk So, Juncheol Shin, Hyunho Kook, Eunhyeok Park |
| 2025 | ICML | Merge-Friendly Post-Training Quantization for Multi-Target Domain Adaptation. | Juncheol Shin, Minsang Seok, Seonggon Kim, Eunhyeok Park |
| 2025 | ISLPED | Partial-Sum Quantization Based on Pseudo-Quantization Noise for Variation-Tolerant Analog In-Memory Computing. | Nameun Kang, Eunhyeok Park, Sangsu Park, Jongil Kim, Jaeyun Yi, Jae-Joon Kim |
| 2025 | WACV | PTQ4VM: Post-Training Quantization for Visual Mamba. | Younghyun Cho, Changhun Lee, Seonggon Kim, Eunhyeok Park |
| 2024 | AAAI | OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Models. | Changhun Lee, Jungyu Jin, Taesu Kim, Hyungjun Kim, Eunhyeok Park |
| 2024 | ACCV | Diffusion Model Compression for Image-to-Image Translation. | Geonung Kim, Beomsu Kim, Eunhyeok Park, Sunghyun Cho |
| 2024 | ECCV | FRDiff : Feature Reuse for Universal Training-Free Acceleration of Diffusion Models. | Junhyuk So, Jungwon Lee, Eunhyeok Park |
| 2024 | EMNLP | QEFT: Quantization for Efficient Fine-Tuning of LLMs. | Changhun Lee, Jungyu Jin, Younghyun Cho, Eunhyeok Park |
| 2024 | MICRO | Low-Overhead General-Purpose Near-Data Processing in CXL Memory Expanders. | Hyungkyu Ham, Jeongmin Hong, Geonwoo Park, Yunseon Shin, Okkyun Woo, Wonhyuk Yang, Jinhoon Bae, Eunhyeok Park, Hyojin Sung, Euicheol Lim, Gwangsun Kim |
| 2023 | CVPR | Multi-scale Local Implicit Keypoint Descriptor for Keypoint Matching. | JongMin Lee, Eunhyeok Park, Sungjoo Yoo |
| 2023 | CVPR | NIPQ: Noise proxy-based Integrated Pseudo-Quantization. | Juncheol Shin, Junhyuk So, Sein Park, Seungyeop Kang, Sungjoo Yoo, Eunhyeok Park |
| 2023 | ICCV | INSTA-BNN: Binary Neural Network with INSTAnce-aware Threshold. | Changhun Lee, Hyungjun Kim, Eunhyeok Park, Jae-Joon Kim |
| 2023 | WACV | Searching for Robust Binary Neural Networks via Bimodal Parameter Perturbation. | Daehyun Ahn, Hyungjun Kim, Taesu Kim, Eunhyeok Park, Jae-Joon Kim |
| 2022 | CC | One-shot tuner for deep learning compilers. | Jaehun Ryu, Eunhyeok Park, Hyojin Sung |
| 2022 | ECCV | BASQ: Branch-wise Activation-clipping Search Quantization for Sub-4-bit Neural Networks. | Han-Byul Kim, Eunhyeok Park, Sungjoo Yoo |
| 2022 | ECCV | Symmetry Regularization and Saturating Nonlinearity for Robust Quantization. | Sein Park, Yeongsang Jang, Eunhyeok Park |
| 2022 | IJCAI | Online Hybrid Lightweight Representations Learning: Its Application to Visual Tracking. | Ilchae Jung, Minji Kim, Eunhyeok Park, Bohyung Han |
| 2021 | ICCV | Fine-grained Semantics-aware Representation Enhancement for Self-supervised Monocular Depth Estimation. | Hyunyoung Jung, Eunhyeok Park, Sungjoo Yoo |
| 2021 | RSP | FPGA Prototyping of Systolic Array-based Accelerator for Low-Precision Inference of Deep Neural Networks. | Soobeom Kim, Seunghwan Cho, Eunhyeok Park, Sungjoo Yoo |
| 2020 | ECCV | PROFIT: A Novel Training Method for sub-4-bit MobileNet Models. | Eunhyeok Park, Sungjoo Yoo |
| 2020 | RecSys | MEANTIME: Mixture of Attention Mechanisms with Multi-temporal Embeddings for Sequential Recommendation. | Sung Min Cho, Eunhyeok Park, Sungjoo Yoo |
| 2019 | ICCV | Tag2Pix: Line Art Colorization Using Text Tag With SECat and Changing Loss. | Hyunsu Kim, Ho Young Jhoo, Eunhyeok Park, Sungjoo Yoo |
| 2018 | ECCV | Value-Aware Quantization for Training and Inference of Neural Networks. | Eunhyeok Park, Sungjoo Yoo, Peter Vajda |
| 2018 | ISCA | Energy-Efficient Neural Network Accelerator Based on Outlier-Aware Low-Precision Computation. | Eunhyeok Park, Dongyoung Kim, Sungjoo Yoo |
| 2017 | CVPR | Weighted-Entropy-Based Quantization for Deep Neural Networks. | Eunhyeok Park, Junwhan Ahn, Sungjoo Yoo |
| 2015 | DATE | Memory fast-forward: a low cost special function unit to enhance energy efficiency in GPU for big data processing. | Eunhyeok Park, Junwhan Ahn, Sungpack Hong, Sungjoo Yoo, Sunggu Lee |