Zhaolin Gao

According to our database, Zhaolin Gao authored at least 15 papers between 2019 and 2025.

Collaborative distances:

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

2025

Prompt Curriculum Learning for Efficient LLM Post-Training.

Zhaolin Gao, Joongwon Kim, Wen Sun, Thorsten Joachims, Sid Wang, Richard Yuanzhe Pang, Liang Tan

CoRR, October, 2025

Pre-trained Large Language Models Learn Hidden Markov Models In-context.

Yijia Dai, Zhaolin Gao, Yahya Sattar, Sarah Dean, Jennifer J. Sun

CoRR, June, 2025

Accelerating RL for LLM Reasoning with Optimal Advantage Regression.

Kianté Brantley, Mingyu Chen, Zhaolin Gao, Jason D. Lee, Wen Sun, Wenhao Zhan, Xuezhou Zhang

CoRR, May, 2025

Value-Guided Search for Efficient Chain-of-Thought Reasoning.

Kaiwen Wang, Jin Peng Zhou, Jonathan D. Chang, Zhaolin Gao, Nathan Kallus, Kianté Brantley, Wen Sun

CoRR, May, 2025

Q♯: Provably Optimal Distributional RL for LLM Post-Training.

Jin Peng Zhou, Kaiwen Wang, Jonathan D. Chang, Zhaolin Gao, Nathan Kallus, Kilian Q. Weinberger, Kianté Brantley, Wen Sun

CoRR, February, 2025

Regressing the Relative Future: Efficient Policy Optimization for Multi-turn RLHF.

Zhaolin Gao, Wenhao Zhan, Jonathan Daniel Chang, Gokul Swamy, Kianté Brantley, Jason D. Lee, Wen Sun

Proceedings of the Thirteenth International Conference on Learning Representations, 2025

LangPTune: Optimizing Language-based User Profiles for Recommendation.

Zhaolin Gao, Joyce Zhou, Yijia Dai, Thorsten Joachims

Proceedings of the 34th ACM International Conference on Information and Knowledge Management, 2025

2024

End-to-end Training for Recommendation with Language-based User Profiles.

Zhaolin Gao, Joyce Zhou, Yijia Dai, Thorsten Joachims

CoRR, 2024

Reviewer2: Optimizing Review Generation Through Prompt Generation.

Zhaolin Gao, Kianté Brantley, Thorsten Joachims

CoRR, 2024

REBEL: Reinforcement Learning via Regressing Relative Rewards.

Zhaolin Gao, Jonathan D. Chang, Wenhao Zhan, Owen Oertell, Gokul Swamy, Kianté Brantley, Thorsten Joachims, Drew Bagnell, Jason D. Lee, Wen Sun

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

2022

MCL: Mixed-Centric Loss for Collaborative Filtering.

Zhaolin Gao, Zhaoyue Cheng, Felipe Pérez, Jianing Sun, Maksims Volkovs

Proceedings of the WWW '22: The ACM Web Conference 2022, Virtual Event, Lyon, France, April 25, 2022

Mitigating the Filter Bubble While Maintaining Relevance: Targeted Diversification with VAE-based Recommender Systems.

Zhaolin Gao, Tianshu Shen, Zheda Mai, Mohamed Reda Bouadjenek, Isaac Waller, Ashton Anderson, Ron Bodkin, Scott Sanner

Proceedings of the SIGIR '22: The 45th International ACM SIGIR Conference on Research and Development in Information Retrieval, Madrid, Spain, July 11, 2022

2020

Guardian: Evaluating Trust in Online Social Networks with Graph Convolutional Networks.

Wanyu Lin, Zhaolin Gao, Baochun Li

Proceedings of the 39th IEEE Conference on Computer Communications, 2020

Shoestring: Graph-Based Semi-Supervised Classification With Severely Limited Labeled Data.

Wanyu Lin, Zhaolin Gao, Baochun Li

Proceedings of the 2020 IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2020

2019

Shoestring: Graph-Based Semi-Supervised Learning with Severely Limited Labeled Data.

Wanyu Lin, Zhaolin Gao, Baochun Li

CoRR, 2019