2024 arXiv REBEL: Reinforcement Learning via Regressing Relative Rewards Gao, Zhaolin, Chang, Jonathan D., Zhan, Wenhao, Oertell, Owen, Swamy, Gokul, Brantley, Kianté, Joachims, Thorsten, Bagnell, J. Andrew, Lee, Jason D., and Sun, Wen In 2024 Code Preprint arXiv Reviewer2: Optimizing Review Generation Through Prompt Generation Gao, Zhaolin, Brantley, Kianté, and Joachims, Thorsten In 2024 Model Code Preprint dataset 2022 RecSys Session-based Recommendation With Transformers Lu, Yichao, Gao, Zhaolin*, Cheng, Zhaoyue*, Sun, Jianing*, Brown, Bradley, Yu, Guangwei, Wong, Anson, Perez, Felipe, and Volkovs, Maksims In Proceedings of the Recommender Systems Challenge 2022 PDF SIGIR Mitigating the Filter Bubble while Maintaining Relevance: Targeted Diversification with VAE-based Recommender Systems Gao, Zhaolin, Shen, Tianshu, Mai, Zheda, Bouadjenek, Mohamed Reda, Waller, Isaac, Anderson, Ashton, Bodkin, Ron, and Sanner, Scott In Proceedings of the 45th International ACM SIGIR Conference 2022 PDF Code WWW MCL: Mixed-Centric Loss for Collaborative Filtering Gao, Zhaolin*, Cheng, Zhaoyue*, Perez, Felipe, Sun, Jianing, and Volkovs, Maksims In Proceedings of the ACM Web Conference 2022 PDF Code 2020 CVPR Shoestring: Graph-Based Semi-Supervised Classification With Severely Limited Labeled Data Lin, Wanyu, Gao, Zhaolin, and Li, Baochun In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition 2020 PDF Code INFOCOM Guardian: Evaluating Trust in Online Social Networks with Graph Convolutional Networks Lin, Wanyu, Gao, Zhaolin, and Li, Baochun In Proceedings of IEEE INFOCOM 2020 PDF Code