Jae Boum Kim

According to our database, Jae Boum Kim authored at least 9 papers between 2021 and 2024.

Collaborative distances:

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

2024

Is Contrastive Learning Necessary? A Study of Data Augmentation vs Contrastive Learning in Sequential Recommendation.

Peilin Zhou, You-Liang Huang, Yueqi Xie, Jingqi Gao, Shoujin Wang, Jae Boum Kim, Sunghun Kim

Proceedings of the ACM on Web Conference 2024, 2024

2023

Exploring Recommendation Capabilities of GPT-4V(ision): A Preliminary Case Study.

Peilin Zhou, Meng Cao, You-Liang Huang, Qichen Ye, Peiyan Zhang, Junling Liu, Yueqi Xie, Yining Hua, Jaeboum Kim

CoRR, 2023

Efficiently Leveraging Multi-level User Intent for Session-based Recommendation via Atten-Mixer Network.

Peiyan Zhang, Jiayan Guo, Chaozhuo Li, Yueqi Xie, Jaeboum Kim, Yan Zhang, Xing Xie, Haohan Wang, Sunghun Kim

Proceedings of the Sixteenth ACM International Conference on Web Search and Data Mining, 2023

Equivariant Contrastive Learning for Sequential Recommendation.

Peilin Zhou, Jingqi Gao, Yueqi Xie, Qichen Ye, Yining Hua, Jaeboum Kim, Shoujin Wang, Sunghun Kim

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Rethinking Multi-Interest Learning for Candidate Matching in Recommender Systems.

Yueqi Xie, Jingqi Gao, Peilin Zhou, Qichen Ye, Yining Hua, Jae Boum Kim, Fangzhao Wu, Sunghun Kim

Proceedings of the 17th ACM Conference on Recommender Systems, 2023

Attention Calibration for Transformer-based Sequential Recommendation.

Peilin Zhou, Qichen Ye, Yueqi Xie, Jingqi Gao, Shoujin Wang, Jae Boum Kim, Chenyu You, Sunghun Kim

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

AdaMCT: Adaptive Mixture of CNN-Transformer for Sequential Recommendation.

Juyong Jiang, Peiyan Zhang, Yingtao Luo, Chaozhuo Li, Jae Boum Kim, Kai Zhang, Senzhang Wang, Xing Xie, Sunghun Kim

Proceedings of the 32nd ACM International Conference on Information and Knowledge Management, 2023

2022

AdaMCT: Adaptive Mixture of CNN-Transformer for Sequential Recommendation.

Juyong Jiang, Jae Boum Kim, Yingtao Luo, Kai Zhang, Sunghun Kim

CoRR, 2022

2021

Sequential Recommendation with Bidirectional Chronological Augmentation of Transformer.

Juyong Jiang, Yingtao Luo, Jae Boum Kim, Kai Zhang, Sunghun Kim

CoRR, 2021