Baeseong Park

According to our database, Baeseong Park authored at least 14 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

DropBP: Accelerating Fine-Tuning of Large Language Models by Dropping Backward Propagation.

Sunghyeon Woo, Baeseong Park, Byeongwook Kim, Minjung Jo, Sejung Kwon, Dongsuk Jeon, Dongsoo Lee

CoRR, 2024

2023

Winning Both the Accuracy of Floating Point Activation and the Simplicity of Integer Arithmetic.

Yulhwa Kim, Jaeyong Jang, Jehun Lee, Jihoon Park, Jeonghoon Kim, Byeongwook Kim, Baeseong Park, Se Jung Kwon, Dongsoo Lee, Jae-Joon Kim

Proceedings of the Eleventh International Conference on Learning Representations, 2023

TF-MVP: Novel Sparsity-Aware Transformer Accelerator with Mixed-Length Vector Pruning.

Eunji Yoo, Gunho Park, Jung Gyu Min, Se Jung Kwon, Baeseong Park, Dongsoo Lee, Youngjoo Lee

Proceedings of the 60th ACM/IEEE Design Automation Conference, 2023

2022

nuQmm: Quantized MatMul for Efficient Inference of Large-Scale Generative Language Models.

Gunho Park, Baeseong Park, Se Jung Kwon, Byeongwook Kim, Youngjoo Lee, Dongsoo Lee

CoRR, 2022

Encoding Weights of Irregular Sparsity for Fixed-to-Fixed Model Compression.

Baeseong Park, Se Jung Kwon, Daehwan Oh, Byeongwook Kim, Dongsoo Lee

Proceedings of the Tenth International Conference on Learning Representations, 2022

AlphaTuning: Quantization-Aware Parameter-Efficient Adaptation of Large-Scale Pre-Trained Language Models.

Se Jung Kwon, Jeonghoon Kim, Jeongin Bae, Kang Min Yoo, Jin-Hwa Kim, Baeseong Park, Byeongwook Kim, Jung-Woo Ha, Nako Sung, Dongsoo Lee

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2022, 2022

2021

Modulating Regularization Frequency for Efficient Compression-Aware Model Training.

Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Jeongin Yun, Baeseong Park, Yongkweon Jeon

CoRR, 2021

Sequential Encryption of Sparse Neural Networks Toward Optimum Representation of Irregular Sparsity.

Baeseong Park, Se Jung Kwon, Dongsoo Lee, Daehwan Oh, Byeongwook Kim, Yongkweon Jeon, Yeonju Ro

CoRR, 2021

Q-Rater: Non-Convex Optimization for Post-Training Uniform Quantization.

Byeongwook Kim, Dongsoo Lee, Yeonju Ro, Yongkweon Jeon, Se Jung Kwon, Baeseong Park, Daehwan Oh

CoRR, 2021

2020

BiQGEMM: matrix multiplication with lookup table for binary-coding-based quantized DNNs.

Yongkweon Jeon, Baeseong Park, Se Jung Kwon, Byeongwook Kim, Jeongin Yun, Dongsoo Lee

Proceedings of the International Conference for High Performance Computing, 2020

FleXOR: Trainable Fractional Quantization.

Dongsoo Lee, Se Jung Kwon, Byeongwook Kim, Yongkweon Jeon, Baeseong Park, Jeongin Yun

Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Extremely Low Bit Transformer Quantization for On-Device Neural Machine Translation.

Insoo Chung, Byeongwook Kim, Yoonjung Choi, Se Jung Kwon, Yongkweon Jeon, Baeseong Park, Sangha Kim, Dongsoo Lee

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2020, 2020

Structured Compression by Weight Encryption for Unstructured Pruning and Quantization.

Se Jung Kwon, Dongsoo Lee, Byeongwook Kim, Parichay Kapoor, Baeseong Park, Gu-Yeon Wei

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Structured Compression by Unstructured Pruning for Sparse Quantized Neural Networks.

Se Jung Kwon, Dongsoo Lee, Byeongwook Kim, Parichay Kapoor, Baeseong Park, Gu-Yeon Wei

CoRR, 2019