Zhengze Zhou

According to our database, Zhengze Zhou authored at least 17 papers between 2018 and 2026.

Collaborative distances:

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

2026

Beyond GRPO and On-Policy Distillation: An Empirical Sparse-to-Dense Reward Principle for Language-Model Post-Training.

Yuanda Xu, Hejian Sang, Zhengze Zhou, Ran He, Zhipeng Wang, Alborz Geramifard

CoRR, May, 2026

TIP: Token Importance in On-Policy Distillation.

Yuanda Xu, Hejian Sang, Zhengze Zhou, Ran He, Zhipeng Wang, Alborz Geramifard

CoRR, April, 2026

Robust Batch-Level Query Routing for Large Language Models under Cost and Capacity Constraints.

Jelena Markovic-Voronov, Kayhan Behdin, Yuanda Xu, Zhengze Zhou, Zhipeng Wang, Rahul Mazumder

CoRR, March, 2026

PACED: Distillation and Self-Distillation at the Frontier of Student Competence.

Yuanda Xu, Hejian Sang, Zhengze Zhou, Ran He, Zhipeng Wang

CoRR, March, 2026

Not all tokens are needed(NAT): token efficient reinforcement learning.

Hejian Sang, Yuanda Xu, Zhengze Zhou, Ran He, Zhipeng Wang

CoRR, March, 2026

On-Policy Self-Distillation for Reasoning Compression.

Hejian Sang, Yuanda Xu, Zhengze Zhou, Ran He, Zhipeng Wang, Jiachen Sun

CoRR, March, 2026

Overconfident Errors Need Stronger Correction: Asymmetric Confidence Penalties for Reinforcement Learning.

Yuanda Xu, Hejian Sang, Zhengze Zhou, Ran He, Zhipeng Wang

CoRR, February, 2026

Semantic Search At LinkedIn.

Fedor Borisyuk, Sriram Vasudevan, Muchen Wu, Guoyao Li, Benjamin Le, Shaobo Zhang, Kay Qianqi Shen, Yuchin Juan, Kayhan Behdin, Liming Dong, Kaixu Yang, Shusen Jing, Ravi Pothamsetty, Rajat Arora, Sophie Yanying Sheng, Vitaly Abdrashitov, Yang Zhao, Lin Su, Xiaoqing Wang, Chujie Zheng, Sarang Metkar, Rupesh Gupta, Igor Lapchuk, David N. Racca, Madhumitha Mohan, Yanbo Li, Haojun Li, Saloni Gandhi, Xueying Lu, Chetan Bhole, Ali Hooshmand, Xin Yang, Raghavan Muthuregunathan, Jiajun Zhang, Mathew Teoh, Adam Coler, Abhinav Gupta, Xiaojing Ma, Sundara Raman Ramachandran, Morteza Ramezani, Yubo Wang, Lijuan Zhang, Richard Li, Jian Sheng, Chanh Nguyen, Yen-Chi Chen, Chuanrui Zhu, Claire Zhang, Jiahao Xu, Deepti Kulkarni, Qing Lan, Arvind Subramaniam, Ata Fatahi Baarzi, Steven Shimizu, Yanning Chen, Zhipeng Wang, Ran He, Zhengze Zhou, Qingquan Song, Yun Dai, Caleb Johnson, Ping Liu, Shaghayegh Gharghabi, Gokulraj Mohanasundaram, Juan Bottaro, Santhosh Sachindran, Qi Guo, Yunxiang Ren, Chengming Jiang, Di Mo, Luke Simon, Jianqiang Shen, Jingwei Wu, Wenjing Zhang

CoRR, February, 2026

Robust Batch-Level Query Routing for Large Language Models under Cost and Capacity Constraints.

Jelena Markovic-Voronov, Kayhan Behdin, Yuanda Xu, Zhengze Zhou, Zhipeng Wang, Rahul Mazumder

Proceedings of the ACM Conference on AI and Agentic Systems, 2026

2024

Approximation trees: statistical reproducibility in model distillation.

Yichen Zhou, Zhengze Zhou, Giles Hooker

Data Min. Knowl. Discov., September, 2024

2022

Examining spatial heterogeneity of ridesourcing demand determinants with explainable machine learning.

Xiaojian Zhang, Xiang Yan, Zhengze Zhou, Yiming Xu, Xilei Zhao

CoRR, 2022

2021

Unbiased Measurement of Feature Importance in Tree-Based Methods.

Zhengze Zhou, Giles Hooker

ACM Trans. Knowl. Discov. Data, 2021

V-statistics and Variance Estimation.

Zhengze Zhou, Lucas Mentch, Giles Hooker

J. Mach. Learn. Res., 2021

S-LIME: Stabilized-LIME for Model Explanation.

Zhengze Zhou, Giles Hooker, Fei Wang

Proceedings of the KDD '21: The 27th ACM SIGKDD Conference on Knowledge Discovery and Data Mining, 2021

2019

Asymptotic Normality and Variance Estimation For Supervised Ensembles.

Zhengze Zhou, Lucas Mentch, Giles Hooker

CoRR, 2019

Distilling Black-Box Travel Mode Choice Model for Behavioral Interpretation.

Xilei Zhao, Zhengze Zhou, Xiang Yan, Pascal Van Hentenryck

CoRR, 2019

2018

Approximation Trees: Statistical Stability in Model Distillation.

Yichen Zhou, Zhengze Zhou, Giles Hooker

CoRR, 2018