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Byeongwook Kim

Structured Compression by Weight Encryption for Unstructured Pruning and Quantization
2020 · Se Jung Kwon, Dongsoo Lee, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 47
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BiQGEMM: Matrix Multiplication with Lookup Table for Binary-Coding-Based Quantized DNNs
2020 · Yongkweon Jeon, Baeseong Park, et al. · 2012 International Conference for High Performance Computing, Networking, Storage and Analysis · 33
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Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation
2020 · Insoo Chung, Byeongwook Kim, et al. · 23
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LUT-GEMM: Quantized Matrix Multiplication based on LUTs for Efficient Inference in Large-Scale Generative Language Models
2022 · Park, Gunho, Park, Baeseong, et al. · arXiv (Cornell University) · 18
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DeepTwist: Learning Model Compression via Occasional Weight Distortion
2018 · Lee, Dongsoo, Kapoor, Parichay, et al. · arXiv (Cornell University) · 16
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Learning Low-Rank Approximation for CNNs
2019 · Lee, Dongsoo, Kwon, Se Jung, et al. · arXiv (Cornell University) · 13
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FleXOR: Trainable Fractional Quantization
2020 · Lee, Dongsoo, Kwon, Se Jung, et al. · arXiv (Cornell University) · 10
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HyperCLOVA X Technical Report
2024 · Yoo, Kang Min, Han, Jaegeun, et al. · arXiv (Cornell University) · 7
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Network Pruning for Low-Rank Binary Indexing
2019 · Lee, Dongsoo, Kwon, Se Jung, et al. · arXiv (Cornell University) · 4
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Computation-Efficient Quantization Method for Deep Neural Networks
2018 · Parichay Kapoor, Dongsoo Lee, et al. · 3
Encoding Weights of Irregular Sparsity for Fixed-to-Fixed Model Compression
2021 · Park, Baeseong, Kwon, Se Jung, et al. · arXiv (Cornell University) · 2
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Unifying Uniform and Binary-coding Quantization for Accurate Compression of Large Language Models
2025 · Seungcheol Park, Jeongin Bae, et al. · Annual Meeting of the Association for Computational Linguistics (ACL) · 1
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No Token Left Behind: Reliable KV Cache Compression via Importance-Aware Mixed Precision Quantization
2024 · Yang, June Yong, Kim, Byeongwook, et al. · arXiv (Cornell University) · 1
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AlphaTuning: Quantization-Aware Parameter-Efficient Adaptation of Large-Scale Pre-Trained Language Models
2022 · Kwon, Se Jung, Kim, Jeonghoon, et al. · arXiv (Cornell University) · 1
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Q-Rater: Non-Convex Optimization for Post-Training Uniform Quantization
2021 · Kim, Byeongwook, Lee, Dongsoo, et al. · arXiv (Cornell University) · 1
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Decoupling Weight Regularization from Batch Size for Model Compression
2019 · Dongsoo Lee, Se Jung Kwon, et al. · 1
CodeGEMM: A Codebook-Centric Approach to Efficient GEMM in Quantized LLMs
2025 · Park, Gunho, Bae, Jeongin, et al. · arXiv (Cornell University)
CodeGEMM: A Codebook-Centric Approach to Efficient GEMM in Quantized LLMs
2025 · Park, Gunho, Bae, Jeongin, et al. · arXiv (Cornell University)
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AnyBCQ: Hardware Efficient Flexible Binary-Coded Quantization for Multi-Precision LLMs
2025 · Park, Gunho, Bae, Jeongin, et al. · arXiv (Cornell University)
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Unifying Uniform and Binary-coding Quantization for Accurate Compression of Large Language Models
2025 · Park, Seungcheol, Bae, Jeongin, et al. · arXiv (Cornell University)
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Faster Inference of LLMs using FP8 on the Intel Gaudi
2025 · Lee, Joonhyung, Markovich-Golan, Shmulik, et al. · arXiv (Cornell University)
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An Inquiry into Datacenter TCO for LLM Inference with FP8
2025 · Kim, Jiwoo, Lee, Joonhyung, et al. · arXiv (Cornell University)
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Modulating Regularization Frequency for Efficient Compression-Aware Model Training
2021 · Lee, Dongsoo, Kwon, Se Jung, et al. · arXiv (Cornell University)
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Sequential Encryption of Sparse Neural Networks Toward Optimum Representation of Irregular Sparsity.
2021 · Baeseong Park, Se Jung Kwon, et al. · arXiv (Cornell University)
Structured Compression by Unstructured Pruning for Sparse Quantized Neural Networks.
2019 · Se Jung Kwon, Dongsoo Lee, et al. · arXiv (Cornell University)
Works count: 25
Citation count: 181
H-index: 7
I10-index: 7
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