Jongwoo Ko - RankMe

39 papers A* 12A 1Journal 24Unranked 2

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	CUA-Skill: Develop Skills for Computer Using Agent. CoRR Tianyi Chen, Yinheng Li, Michael Solodko, Sen Wang, Nan Jiang, Tingyuan Cui, Junheng Hao, Jongwoo Ko, Sara Abdali, Suzhen Zheng, Leon Xu, Hao Fan, Pashmina Cameron, Justin Wagle, Kazuhito Koishida
2026	J	`jnl`	Scaling Reasoning Efficiently via Relaxed On-Policy Distillation. CoRR Jongwoo Ko, Sara Abdali, Young Jin Kim, Tianyi Chen, Pashmina Cameron
2026	J	`jnl`	StableQAT: Stable Quantization-Aware Training at Ultra-Low Bitwidths. CoRR Tianyi Chen, Sihan Chen, Xiaoyi Qu, Dan Zhao, Ruomei Yan, Jongwoo Ko, Luming Liang, Pashmina Cameron
2025	J	`jnl`	AppSelectBench: Application-Level Tool Selection Benchmark. CoRR Tianyi Chen, Michael Solodko, Sen Wang, Jongwoo Ko, Junheng Hao, Colby R. Banbury, Sara Abdali, Saeed Amizadeh, Qing Xiao, Yinheng Li, Tianyu Ding, Kamran Ghasedi Dizaji, Suzhen Zheng, Hao Fan, Justin Wagle, Pashmina Cameron, Kazuhito Koishida
2025	A	`conf`	Bayesian Principles Improve Prompt Learning In Vision-Language Models. AISTATS Mingyu Kim, Jongwoo Ko, Mijung Park
2025	J	`jnl`	Bayesian Principles Improve Prompt Learning In Vision-Language Models. CoRR Mingyu Kim, Jongwoo Ko, Mijung Park
2025	A*	`conf`	Beyond correlation: The impact of human uncertainty in measuring the effectiveness of automatic evaluation and LLM-as-a-judge. ICLR Aparna Elangovan, Lei Xu, Jongwoo Ko, Mahsa Elyasi, Ling Liu, Sravan Babu Bodapati, Dan Roth
2025	A*	`conf`	DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs. ICML Jongwoo Ko, Tianyi Chen, Sungnyun Kim, Tianyu Ding, Luming Liang, Ilya Zharkov, Se-Young Yun
2025	J	`jnl`	DistiLLM-2: A Contrastive Approach Boosts the Distillation of LLMs. CoRR Jongwoo Ko, Tianyi Chen, Sungnyun Kim, Tianyu Ding, Luming Liang, Ilya Zharkov, Se-Young Yun
2025	J	`jnl`	Flex-Judge: Think Once, Judge Anywhere. CoRR Jongwoo Ko, Sungnyun Kim, Sungwoo Cho, Se-Young Yun
2025	J	`jnl`	Revisiting Multi-Agent Debate as Test-Time Scaling: A Systematic Study of Conditional Effectiveness. CoRR Yongjin Yang, Euiin Yi, Jongwoo Ko, Kimin Lee, Zhijing Jin, Se-Young Yun
2025	A*	`conf`	SeRA: Self-Reviewing and Alignment of LLMs using Implicit Reward Margins. ICLR Jongwoo Ko, Saket Dingliwal, Bhavana Ganesh, Sailik Sengupta, Sravan Babu Bodapati, Aram Galstyan
2025	J	`jnl`	WINA: Weight Informed Neuron Activation for Accelerating Large Language Model Inference. CoRR Sihan Chen, Dan Zhao, Jongwoo Ko, Colby R. Banbury, Huiping Zhuang, Luming Liang, Tianyi Chen
2025	J	`jnl`	When Debate Fails: Bias Reinforcement in Large Language Models. CoRR Jihwan Oh, Minchan Jeong, Jongwoo Ko, Se-Young Yun
2024	J	`jnl`	Beyond correlation: The impact of human uncertainty in measuring the effectiveness of automatic evaluation and LLM-as-a-judge. CoRR Aparna Elangovan, Jongwoo Ko, Lei Xu, Mahsa Elyasi, Ling Liu, Sravan Bodapati, Dan Roth
2024	A*	`conf`	DistiLLM: Towards Streamlined Distillation for Large Language Models. ICML Jongwoo Ko, Sungnyun Kim, Tianyi Chen, Se-Young Yun
2024	J	`jnl`	DistiLLM: Towards Streamlined Distillation for Large Language Models. CoRR Jongwoo Ko, Sungnyun Kim, Tianyi Chen, Se-Young Yun
2024	A*	`conf`	Fine-tuning Pre-trained Models for Robustness under Noisy Labels. IJCAI Sumyeong Ahn, Sihyeon Kim, Jongwoo Ko, Se-Young Yun
2024	J	`jnl`	HESSO: Towards Automatic Efficient and User Friendly Any Neural Network Training and Pruning. CoRR Tianyi Chen, Xiaoyi Qu, David Aponte, Colby R. Banbury, Jongwoo Ko, Tianyu Ding, Yong Ma, Vladimir Lyapunov, Ilya Zharkov, Luming Liang
2024	J	`jnl`	SeRA: Self-Reviewing and Alignment of Large Language Models using Implicit Reward Margins. CoRR Jongwoo Ko, Saket Dingliwal, Bhavana Ganesh, Sailik Sengupta, Sravan Bodapati, Aram Galstyan
2024	A*	`conf`	Towards Difficulty-Agnostic Efficient Transfer Learning for Vision-Language Models. EMNLP Yongjin Yang, Jongwoo Ko, Se-Young Yun
2023	A*	`conf`	A Gift from Label Smoothing: Robust Training with Adaptive Label Smoothing via Auxiliary Classifier under Label Noise. AAAI Jongwoo Ko, Bongsoo Yi, Se-Young Yun
2023	J	`jnl`	CUDA: Curriculum of Data Augmentation for Long-Tailed Recognition. CoRR Sumyeong Ahn, Jongwoo Ko, Se-Young Yun
2023	A*	`conf`	CUDA: Curriculum of Data Augmentation for Long-tailed Recognition. ICLR Sumyeong Ahn, Jongwoo Ko, Se-Young Yun
2023	A*	`conf`	Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding. EMNLP Sangmin Bae, Jongwoo Ko, Hwanjun Song, Se-Young Yun
2023	J	`jnl`	Fast and Robust Early-Exiting Framework for Autoregressive Language Models with Synchronized Parallel Decoding. CoRR Sangmin Bae, Jongwoo Ko, Hwanjun Song, Se-Young Yun
2023	J	`jnl`	Fine tuning Pre trained Models for Robustness Under Noisy Labels. CoRR Sumyeong Ahn, Sihyeon Kim, Jongwoo Ko, Se-Young Yun
2023	J	`jnl`	Improving Adaptability and Generalizability of Efficient Transfer Learning for Vision-Language Models. CoRR Yongjin Yang, Jongwoo Ko, Se-Young Yun
2023	—	`conf`	NASH: A Simple Unified Framework of Structured Pruning for Accelerating Encoder-Decoder Language Models. EMNLP (Findings) Jongwoo Ko, Seungjoon Park, Yujin Kim, Sumyeong Ahn, Du-Seong Chang, Euijai Ahn, Se-Young Yun
2023	J	`jnl`	NASH: A Simple Unified Framework of Structured Pruning for Accelerating Encoder-Decoder Language Models. CoRR Jongwoo Ko, Seungjoon Park, Yujin Kim, Sumyeong Ahn, Du-Seong Chang, Euijai Ahn, Se-Young Yun
2023	—	`conf`	Revisiting Intermediate Layer Distillation for Compressing Language Models: An Overfitting Perspective. EACL (Findings) Jongwoo Ko, Seungjoon Park, Minchan Jeong, Sukjin Hong, Euijai Ahn, Du-Seong Chang, Se-Young Yun
2023	J	`jnl`	Revisiting Intermediate Layer Distillation for Compressing Language Models: An Overfitting Perspective. CoRR Jongwoo Ko, Seungjoon Park, Minchan Jeong, Sukjin Hong, Euijai Ahn, Du-Seong Chang, Se-Young Yun
2023	A*	`conf`	Self-Contrastive Learning: Single-Viewed Supervised Contrastive Framework Using Sub-network. AAAI Sangmin Bae, Sungnyun Kim, Jongwoo Ko, Gihun Lee, Seungjong Noh, Se-Young Yun
2022	J	`jnl`	ALASCA: Rethinking Label Smoothing for Deep Learning Under Label Noise. CoRR Jongwoo Ko, Bongsoo Yi, Se-Young Yun
2022	A*	`conf`	Synergy with Translation Artifacts for Training and Inference in Multilingual Tasks. EMNLP Jaehoon Oh, Jongwoo Ko, Se-Young Yun
2022	J	`jnl`	Synergy with Translation Artifacts for Training and Inference in Multilingual Tasks. CoRR Jaehoon Oh, Jongwoo Ko, Se-Young Yun
2021	A*	`conf`	FINE Samples for Learning with Noisy Labels. NeurIPS Taehyeon Kim, Jongwoo Ko, Sangwook Cho, Jinhwan Choi, Se-Young Yun
2021	J	`jnl`	FINE Samples for Learning with Noisy Labels. CoRR Taehyeon Kim, Jongwoo Ko, Jinhwan Choi, Sangwook Cho, Se-Young Yun
2021	J	`jnl`	Self-Contrastive Learning. CoRR Sangmin Bae, Sungnyun Kim, Jongwoo Ko, Gihun Lee, Seungjong Noh, Se-Young Yun