Jungyu Jin

According to our database, Jungyu Jin authored at least 7 papers between 2023 and 2025.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2025

SEAL: Scaling to Emphasize Attention for Long-Context Retrieval.

Changhun Lee, Jungyu Jin, Younghyun Cho, Eunhyeok Park

CoRR, January, 2025

PruneCD: Contrasting Pruned Self Model to Improve Decoding Factuality.

Byeongho Yu, Changhun Lee, Jungyu Jin, Eunhyeok Park

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

AMQ: Enabling AutoML for Mixed-precision Weight-Only Quantization of Large Language Models.

Sangjun Lee, Seung-taek Woo, Jungyu Jin, Changhun Lee, Eunhyeok Park

Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing, 2025

SEAL: Scaling to Emphasize Attention for Long-Context Retrieval.

Changhun Lee, Minsang Seok, Jungyu Jin, Younghyun Cho, Eunhyeok Park

Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2025

2024

QEFT: Quantization for Efficient Fine-Tuning of LLMs.

Changhun Lee, Jungyu Jin, Younghyun Cho, Eunhyeok Park

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2024, 2024

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

Proceedings of the Thirty-Eighth AAAI Conference on Artificial Intelligence, 2024

2023

OWQ: Lessons learned from activation outliers for weight quantization in large language models.

Changhun Lee, Jungyu Jin, Taesu Kim, Hyungjun Kim, Eunhyeok Park

CoRR, 2023