Jongwoo Ko

According to our database, Jongwoo Ko authored at least 17 papers between 2021 and 2024.

Collaborative distances:

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

2024

SeRA: Self-Reviewing and Alignment of Large Language Models using Implicit Reward Margins.

Jongwoo Ko, Saket Dingliwal, Bhavana Ganesh, Sailik Sengupta, Sravan Bodapati, Aram Galstyan

CoRR, 2024

Beyond correlation: The impact of human uncertainty in measuring the effectiveness of automatic evaluation and LLM-as-a-judge.

Aparna Elangovan, Jongwoo Ko, Lei Xu, Mahsa Elyasi, Ling Liu, Sravan Bodapati, Dan Roth

CoRR, 2024

HESSO: Towards Automatic Efficient and User Friendly Any Neural Network Training and Pruning.

Tianyi Chen, Xiaoyi Qu, David Aponte, Colby R. Banbury, Jongwoo Ko, Tianyu Ding, Yong Ma, Vladimir Lyapunov, Ilya Zharkov, Luming Liang

CoRR, 2024

Fine-tuning Pre-trained Models for Robustness under Noisy Labels.

Sumyeong Ahn, Sihyeon Kim, Jongwoo Ko, Se-Young Yun

Proceedings of the Thirty-Third International Joint Conference on Artificial Intelligence, 2024

DistiLLM: Towards Streamlined Distillation for Large Language Models.

Jongwoo Ko, Sungnyun Kim, Tianyi Chen, Se-Young Yun

Proceedings of the Forty-first International Conference on Machine Learning, 2024

Towards Difficulty-Agnostic Efficient Transfer Learning for Vision-Language Models.

Yongjin Yang, Jongwoo Ko, Se-Young Yun

Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing, 2024

2023

Improving Adaptability and Generalizability of Efficient Transfer Learning for Vision-Language Models.

Yongjin Yang, Jongwoo Ko, Se-Young Yun

CoRR, 2023

CUDA: Curriculum of Data Augmentation for Long-tailed Recognition.

Sumyeong Ahn, Jongwoo Ko, Se-Young Yun

Proceedings of the Eleventh International Conference on Learning Representations, 2023

NASH: A Simple Unified Framework of Structured Pruning for Accelerating Encoder-Decoder Language Models.

Jongwoo Ko, Seungjoon Park, Yujin Kim, Sumyeong Ahn, Du-Seong Chang, Euijai Ahn, Se-Young Yun

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding.

Sangmin Bae, Jongwoo Ko, Hwanjun Song, Se-Young Yun

Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing, 2023

Revisiting Intermediate Layer Distillation for Compressing Language Models: An Overfitting Perspective.

Jongwoo Ko, Seungjoon Park, Minchan Jeong, Sukjin Hong, Euijai Ahn, Du-Seong Chang, Se-Young Yun

Proceedings of the Findings of the Association for Computational Linguistics: EACL 2023, 2023

A Gift from Label Smoothing: Robust Training with Adaptive Label Smoothing via Auxiliary Classifier under Label Noise.

Jongwoo Ko, Bongsoo Yi, Se-Young Yun

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

Self-Contrastive Learning: Single-Viewed Supervised Contrastive Framework Using Sub-network.

Sangmin Bae, Sungnyun Kim, Jongwoo Ko, Gihun Lee, Seungjong Noh, Se-Young Yun

Proceedings of the Thirty-Seventh AAAI Conference on Artificial Intelligence, 2023

2022

ALASCA: Rethinking Label Smoothing for Deep Learning Under Label Noise.

Jongwoo Ko, Bongsoo Yi, Se-Young Yun

CoRR, 2022

Synergy with Translation Artifacts for Training and Inference in Multilingual Tasks.

Jaehoon Oh, Jongwoo Ko, Se-Young Yun

Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022

2021

Self-Contrastive Learning.

Sangmin Bae, Sungnyun Kim, Jongwoo Ko, Gihun Lee, Seungjong Noh, Se-Young Yun

CoRR, 2021

FINE Samples for Learning with Noisy Labels.

Taehyeon Kim, Jongwoo Ko, Sangwook Cho, Jinhwan Choi, Se-Young Yun

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021