Taeyoung Yun

According to our database, Taeyoung Yun authored at least 15 papers between 2023 and 2025.

Collaborative distances:

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

2025

Diffusion Alignment as Variational Expectation-Maximization.

Jaewoo Lee, Minsu Kim, Sanghyeok Choi, Inhyuck Song, Sujin Yun, Hyeongyu Kang, Woocheol Shin, Taeyoung Yun, Kiyoung Om, Jinkyoo Park

CoRR, October, 2025

Active Attacks: Red-teaming LLMs via Adaptive Environments.

Taeyoung Yun, Pierre-Luc St-Charles, Jinkyoo Park, Yoshua Bengio, Minsu Kim

CoRR, September, 2025

Posterior Inference in Latent Space for Scalable Constrained Black-box Optimization.

Kiyoung Om, Kyuil Sim, Taeyoung Yun, Hyeongyu Kang, Jinkyoo Park

CoRR, July, 2025

Offline Model-Based Optimization: Comprehensive Review.

Minsu Kim, Jiayao Gu, Ye Yuan, Taeyoung Yun, Zixuan Liu, Yoshua Bengio, Can Chen

CoRR, March, 2025

Wind Farm Layout Optimization with Diffusion Models.

Yujin Shin, Taeyoung Yun, Sujin Yun, Sungpil Woo, Sunhwan Lim, Jinkyoo Park

Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.2, 2025

Posterior Inference with Diffusion Models for High-dimensional Black-box Optimization.

Taeyoung Yun, Kiyoung Om, Jaewoo Lee, Sujin Yun, Jinkyoo Park

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Improved Off-policy Reinforcement Learning in Biological Sequence Design.

Hyeonah Kim, Minsu Kim, Taeyoung Yun, Sanghyeok Choi, Emmanuel Bengio, Alex Hernández-García, Jinkyoo Park

Proceedings of the Forty-second International Conference on Machine Learning, 2025

Adaptive teachers for amortized samplers.

Minsu Kim, Sanghyeok Choi, Taeyoung Yun, Emmanuel Bengio, Leo Feng, Jarrid Rector-Brooks, Sungsoo Ahn, Jinkyoo Park, Nikolay Malkin, Yoshua Bengio

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Learning to Sample Effective and Diverse Prompts for Text-to-Image Generation.

Taeyoung Yun, Dinghuai Zhang, Jinkyoo Park, Ling Pan

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

2024

Guided Trajectory Generation with Diffusion Models for Offline Model-based Optimization.

Taeyoung Yun, Sujin Yun, Jaewoo Lee, Jinkyoo Park

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

GTA: Generative Trajectory Augmentation with Guidance for Offline Reinforcement Learning.

Jaewoo Lee, Sujin Yun, Taeyoung Yun, Jinkyoo Park

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

An Offline Meta Black-box Optimization Framework for Adaptive Design of Urban Traffic Light Management Systems.

Taeyoung Yun, Kanghoon Lee, Sujin Yun, Ilmyung Kim, Won-Woo Jung, Min-Cheol Kwon, Kyujin Choi, Yoohyeon Lee, Jinkyoo Park

Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2024

Learning to Scale Logits for Temperature-Conditional GFlowNets.

Minsu Kim, Joohwan Ko, Taeyoung Yun, Dinghuai Zhang, Ling Pan, Woochang Kim, Jinkyoo Park, Emmanuel Bengio, Yoshua Bengio

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

Local Search GFlowNets.

Minsu Kim, Taeyoung Yun, Emmanuel Bengio, Dinghuai Zhang, Yoshua Bengio, Sungsoo Ahn, Jinkyoo Park

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Learning to Scale Logits for Temperature-Conditional GFlowNets.

Minsu Kim, Joohwan Ko, Dinghuai Zhang, Ling Pan, Taeyoung Yun, Woochang Kim, Jinkyoo Park, Yoshua Bengio

CoRR, 2023