Sungyub Kim

According to our database, Sungyub Kim authored at least 9 papers between 2019 and 2024.

Collaborative distances:

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

2024

LANTERN: Accelerating Visual Autoregressive Models with Relaxed Speculative Decoding.

Doohyuk Jang, Sihwan Park, June Yong Yang, Yeonsung Jung, Jihun Yun, Souvik Kundu, Sungyub Kim, Eunho Yang

CoRR, 2024

A Simple Remedy for Dataset Bias via Self-Influence: A Mislabeled Sample Perspective.

Yeonsung Jung, Jaeyun Song, June Yong Yang, Jin-Hwa Kim, Sungyub Kim, Eunho Yang

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

TTD: Text-Tag Self-Distillation Enhancing Image-Text Alignment in CLIP to Alleviate Single Tag Bias.

Sanghyun Jo, Soohyun Ryu, Sungyub Kim, Eunho Yang, Kyungsu Kim

Proceedings of the Computer Vision - ECCV 2024, 2024

2023

GEX: A flexible method for approximating influence via Geometric Ensemble.

Sungyub Kim, Kyungsu Kim, Eunho Yang

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

RGE: A Repulsive Graph Rectification for Node Classification via Influence.

Jaeyun Song, Sungyub Kim, Eunho Yang

Proceedings of the International Conference on Machine Learning, 2023

Scale-invariant Bayesian Neural Networks with Connectivity Tangent Kernel.

Sungyub Kim, Sihwan Park, Kyung-Su Kim, Eunho Yang

Proceedings of the Eleventh International Conference on Learning Representations, 2023

2020

Generalized Tsallis Entropy Reinforcement Learning and Its Application to Soft Mobile Robots.

Kyungjae Lee, Sungyub Kim, Sungbin Lim, Sungjoon Choi, Mineui Hong, Jae In Kim, Yong-Lae Park, Songhwai Oh

Proceedings of the Robotics: Science and Systems XVI, 2020

2019

Reliable Estimation of Individual Treatment Effect with Causal Information Bottleneck.

Sungyub Kim, Yongsu Baek, Sung Ju Hwang, Eunho Yang

CoRR, 2019

Tsallis Reinforcement Learning: A Unified Framework for Maximum Entropy Reinforcement Learning.

Kyungjae Lee, Sungyub Kim, Sungbin Lim, Sungjoon Choi, Songhwai Oh

CoRR, 2019