2026

[W9] Eliciting Weak-to-Strong Generalization with On-Policy Reverse Distillation

• Youngrok Park*, Sangmin Bae*, Hojung Jung, Jongwoo Ko, Yunseon Choi, Young Jin Kim, Pashmina Cameron, Aaron Courville, Se-Young Yun

• NeurIPS 2026 Workshop on Continual Learning in the Era of Foundation Models and Embodied Agents (CL4FMAgents). 2026. Sydney [paper]

[C18/W8] Scaling Reasoning Efficiently via Relaxed On-Policy Distillation

• Jongwoo Ko, Sara Abdali, Young Jin Kim, Tianyi Chen, Pashmina Cameron

• The Fortieth Annual Conference on Neural Information Processing Systems (NeurIPS). 2026. Sydney

• ICML 2026 Workshop on Resource-Adaptive Foundation Model Inference (AdaptFM). 2026. Seoul [paper]

[W7] CUA-Skill: Develop Skills for Computer Using Agent

• Tianyi Chen*, Yinheng Li*, Michael Solodko*, Sen Wang*, Nan Jiang, Junheng Hao, Tigyuan Cui, Jongwoo Ko, Sara Abdali, Suzhen Zheng, Pashmina Cameron, Justin Wagle, Kazuhito Koishida

• ICML 2026 Workshop on Compositional Learning: Safety, Interpretability, and Agents (CompLearn). 2026. Seoul [paper]

[C17/W6] WINA: Weighted Informed Neuron Activation for Accelerating Large Language Model Inference

• Sihan Chen, Dan Zhao, Jongwoo Ko, Colby Banbury, Huiping Zhuang, Luming Liang, Pashmina Cameron, Tianyi Chen

• The Fourteenth International Conference on Learning Representations (ICLR). 2026. Rio de Janeiro

• ICML 2025 Workshop ES-FoMo-III (ES-FoMo-III). 2025. Vancouver [paper] [code]

[J3/W5] From Belief Entrenchment to Robust Reasoning in LLM Agents

• Jihwan Oh*, Minchan Jeong*, Jongwoo Ko^, Se-Young Yun^

• [J3] Transactions of the Association for Computational Linguistics (TACL)

• [W5] When Debate Fails: Bias Reinforcement in Large Language Models

  • ICLR 2025 Workshop on Reasoning and Planning for Large Language Models. 2025. Singapore [paper] [website]

2025

[C16/W8] Flex-Judge: Text-Only Reasoning Unleashes Zero-Shot Multimodal Evaluators

• Jongwoo Ko*, Sungnyun Kim*, Sungwoo Cho, Se-Young Yun

• The Thirty-Ninth Annual Conference on Neural Information Processing Systems (NeurIPS). 2025. San Diego [paper] [code]

• 1st Workshop on Knowledge-Intensive Multimodal Reasoning (KnowledgeMR) @ICCV 2025 . 2025. Hawaii [paper] [code]

[W7] Revisiting Multi-Agent Debate as Test-Time Scaling: A Systematic Study of Conditional Effectiveness

• Yongjin Yang*, Euiin Yi*, Jongwoo Ko, Kimin Lee, Zhijing Jin, Se-Young Yun

• ICML 2025 Workshop on Multi-Agent Systems (MAS). 2025. Vancouver [paper] [code]

[C15] DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs

• Jongwoo Ko, Tianyi Chen, Sungnyun Kim, Tianyu Ding, Luming Liang, Ilya Zharkov, Se-Young Yun

• The Forty-Second International Conference on Machine Learning (ICML). 2025. Vancouver (Oral Presentation; 120/12107 = top ~1%) [paper] [code]

[C14] SeRA: Self-Reviewing and Alignment of LLMs using Implicit Reward Margins

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

• The Thirteenth International Conference on Learning Representations (ICLR). 2025. Singapore [paper]

[C13] Beyond Correlation: The Impact of Human Uncertainty in Measuring the Effectiveness of Automatic Evaluation and LLM-as-a-Judge

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

• The Thirteenth International Conference on Learning Representations (ICLR). 2025. Singapore [paper]

[C12] Bayesian Principles Improve Prompt Learning in Vision-Language Models

• Mingyu Kim*, Jongwoo Ko*, Mi-Jung Park

• The 28th International Conference on Artificial Intelligence and Statistics (AISTATS). 2025. Thailand [paper] [code]

2024

[C11] Towards Difficulty-Agnostic Efficient Transfer Learning for Vision-Language Models

• Yongjin Yang*, Jongwoo Ko*, Se-Young Yun. 

• The 2024 Conference on Empirical Methods in Natural Language Processing (EMNLP). 2024. Miami [paper] [code]

[C10] DistiLLM: Towards Streamlined Distillation for Large Language Models 

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

• The Forty-first International Conference on Machine Learning (ICML). 2024. Vienna [paper] [code (200+⭐)]

• Selected as a WINNER in Qualcomm Innovation Fellowship Korea 2024 (QIFK 2024)

[C9] Fine-tuning Pre-trained Models for Robustness Under Noisy Labels

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

• International Joint Conference on Artificial Intelligence (IJCAI). 2024. Jeju [paper]

2023

[C8] 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^

• Findings of the Association for Computational Linguistics: EMNLP 2023 (Findings of EMNLP). 2023. Singapore [paper] [code]

[C7] Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding

• Sangmin Bae*, Jongwoo Ko*, Hwanjun Song^, Se-Young Yun^

• The 2023 Conference on Empirical Methods in Natural Language Processing (EMNLP). 2023. Singapore [paper] [code (50+⭐)]

• 🥈 Silver Prize, 30th Samsung Humantech Paper Awards

[W4] Efficient Utilization of Pre-trained Model for Learning with Noisy Labels

• Jongwoo Ko*, Sumyeong Ahn*, Se-Young Yun

• ICLR 2023 Workshop on Pitfalls of Limited Data and Computation for Trustworthy ML (TrustML). 2023. Kigali (Oral Presentation) [paper] [website]

[C6] Revisiting Intermediate Layer Distillation for Compressing Language Models: An Overfitting Perspective 

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

• Findings of the Association for Computational Linguistics: EACL 2023 (Findings of EACL). 2023. Dubrovnik [paper] [code]

[C5/W2/W3] CUDA: Curriculum of Data Augmentation for Long-tailed Recognition

• Sumyeong Ahn*, Jongwoo Ko*, Se-Young Yun

• [C5] The Eleventh International Conference on Learning Representations (ICLR). 2023. Kigali. (Notable-Top-25%) [paper] [code]

• [W2] NeurIPS 2022 Workshop on Distribution Shifts (DistShift). 2022. New Orleans [paper] [website]

• [W3] NeurIPS 2022 ML Safety Workshop (MLSW). 2022. New Orleans [paper] [website]

[C4] Self-Contrastive Learning: Single-viewed Supervised Contrastive Framework using Sub-network

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

• Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI). 2023. Washington, D.C. (Oral Presentation) [paper] [code]

[C3/W1] A Gift from Label Smoothing: Robust Training with Adaptive Label Smoothing via Auxiliary Classifier under Label Noise

• Jongwoo Ko*, Bongsoo Yi*, Se-Young Yun.

• [C3] Thirty-Seventh AAAI Conference on Artificial Intelligence (AAAI). 2023. Washington, D.C. [paper] [code]

• [W1] ALASCA: Rethinking Label Smoothing for Deep Learning Under Label Noise

  • ICML 2022 Workshop on Principles of Distribution Shift (PODS). 2022. Baltimore [paper] [website]

2022

[C2] Synergy with Translation Artifacts for Training and Inference in Multilingual Tasks

• Jaehoon Oh*, Jongwoo Ko*, Se-Young Yun.

•  The 2022 Conference on Empirical Methods in Natural Language Processing (EMNLP). 2022. Abu Dhabi [paper] [code]

[J2] Deep Learning-Based Cataract Detection and Grading from Slit-Lamp and Retro-Illumination Photographs: Model Development and Validation Study

• Ki Young Son*, Jongwoo Ko*, Eunseok Kim, Si Young Lee, Min-Ji Kim, Jisang Han, Eunhae Shin, Tae-Young Chung, Dong Hui Lim

• Ophthalmology Science. 2(2). 100147 [paper]

2021

[C1] FINE Samples for Learning with Noisy Labels

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

• The Thirty-Fifth Annual Conference on Neural Information Processing Systems (NeurIPS). 2021. Virtual [paper] [code]

• Selected as a WINNER in Qualcomm Innovation Fellowship Korea 2022 (QIFK 2022)