Yonsei University’s School of Computing Has 12 Papers Accepted at ICLR 2025

Professors from Yonsei University’s School of Computing have had 12 papers accepted at the International Conference on Learning Representations (ICLR) 2025.

ICLR is a top-tier international conference that focuses on cutting-edge research in deep learning and representation learning. Every year, AI experts from around the world gather to share groundbreaking research findings. With this achievement, Yonsei University’s School of Computing has once again demonstrated its global research competitiveness and contributed to elevating the status of Korean AI research on the international stage.

List of accepted papers:

1. Adaptive Energy Alignment for Accelerating Test-Time Adaptation

- Wonjeong Choi, Do-Yeon Kim, Jungwuk Park, Jungmoon Lee, Younghyun Park, Dong-Jun Han, and Jaekyun Moon

2. Anti-Exposure Bias in Diffusion Models via Prompt Learning (Spotlight Presentation)

- Junyu Zhang, Daochang Liu, Eunbyung Park, Shichao Zhang, Chang Xu

3. Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis

- Guangchen Lan, Dong-Jun Han, Abolfazl Hashemi, Vaneet Aggarwal, Christopher G. Brinton

4. Decentralized Sporadic Federated Learning: A Unified Algorithmic Framework with Convergence Guarantees (Spotlight Presentation)

- Shahryar Zehtabi, Dong-Jun Han, Rohit Parasnis, Seyyedali Hosseinalipour, Christopher G. Brinton

5. Model-based Offline Reinforcement Learning with Lower Expectile Q-Learning

- Kwanyoung Park, Youngwoon Lee

6. PIG: Physics-Informed Gaussians as Adaptive Parametric Mesh Representations

- Namgyu Kang*, Jaemin Oh*, Youngjoon Hong, Eunbyung Park

7. PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models

- Kyeongkook Seo, Dong-Jun Han*, Jaejun Yoo*

8. See What You Are Told: Visual Attention Sink in Large Multimodal Models

- Seil Kang*, Jinyeong Kim*, Junhyeok Kim, Seong Jae Hwang

9. SEMDICE: Off-policy State Entropy Maximization via Stationary Distribution Correction Estimation

- Jongmin Lee*, Meiqi Sun*, Pieter Abbeel

10. Spread Preference Annotation: Direct Preference Judgment for Efficient LLM Alignment (Oral Presentation (207/11672=1.77%))

- Dongyoung Kim, Kimin Lee, Jinwoo Shin, and Jaehyung Kim

11. Unlocking the Potential of Model Calibration in Federated Learning

- Yun-Wei Chu, Dong-Jun Han, Seyyedali Hosseinalipour, Christopher G. Brinton

12. Web Agents with World Models: Learning and Leveraging Environment Dynamics in Web Navigation

- Hyungjoo Chae, Namyoung Kim, Kai Tzu-iunn Ong, Minju Gwak, Gwanwoo Song, Jihoon Kim, Sunghwan Kim, Dongha Lee, Jinyoung Yeo

Image Source: ICLR Official Website (https://iclr.cc)