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ORCIDBanghua Zhu
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2020 – today
- 2025
[c23]Ziao Wang, Nadim Ghaddar, Banghua Zhu, Lele Wang:
Noisy Computing of the Threshold Function. ALT 2025: 1313-1315- [c22]Evan Frick, Tianle Li, Connor Chen, Wei-Lin Chiang, Anastasios Nikolas Angelopoulos, Jiantao Jiao, Banghua Zhu, Joseph E. Gonzalez, Ion Stoica:
How to Evaluate Reward Models for RLHF. ICLR 2025 - [c21]Jixuan Leng, Chengsong Huang, Banghua Zhu, Jiaxin Huang:
Taming Overconfidence in LLMs: Reward Calibration in RLHF. ICLR 2025 - [i41]Jihan Yao, Yushi Hu, Yujie Yi, Bin Han, Shangbin Feng, Guang Yang, Bingbing Wen, Ranjay Krishna, Lucy Lu Wang, Yulia Tsvetkov, Noah A. Smith, Banghua Zhu:
MMMG: a Comprehensive and Reliable Evaluation Suite for Multitask Multimodal Generation. CoRR abs/2505.17613 (2025) - [i40]Jiaxuan Gao, Wei Fu, Minyang Xie, Shusheng Xu, Chuyi He, Zhiyu Mei, Banghua Zhu, Yi Wu:
Beyond Ten Turns: Unlocking Long-Horizon Agentic Search with Large-Scale Asynchronous RL. CoRR abs/2508.07976 (2025) - [i39]Aarti Basant, Abhijit Khairnar, Abhijit Paithankar, Abhinav Khattar, Adithya Renduchintala, Aditya Malte, Akhiad Bercovich, Akshay Hazare, Alejandra Rico, Aleksander Ficek, Alex Kondratenko, Alex Shaposhnikov, Alexander Bukharin, Ali Taghibakhshi, Amelia Barton, Ameya Sunil Mahabaleshwarkar, Amy Shen, Andrew Tao, Ann Guan, Anna Shors, Anubhav Mandarwal, Arham Mehta, Arun Venkatesan, Ashton Sharabiani, Ashwath Aithal, Ashwin Poojary, Ayush Dattagupta, Balaram Buddharaju, Banghua Zhu, Barnaby Simkin, Bilal Kartal, Bita Darvish Rouhani, Bobby Chen, Boris Ginsburg, Brandon Norick, Brian Yu, Bryan Catanzaro, Charles Wang, Charlie Truong, Chetan Mungekar, Chintan Patel, Chris Alexiuk, Christian Munley, Christopher Parisien, Dan Su, Daniel Afrimi, Daniel Korzekwa, Daniel Rohrer, Daria Gitman, David Mosallanezhad, Deepak Narayanan, Dima Rekesh, Dina Yared, Dmytro Pykhtar, Dong Ahn, Duncan Riach, Eileen Long, Elliott Ning, Eric Chung, Erick Galinkin, Evelina Bakhturina, Gargi Prasad, Gerald Shen, Haifeng Qian, Haim Elisha, Harsh Sharma, Hayley Ross, Helen Ngo, Herman Sahota, Hexin Wang, Hoo Chang Shin, Hua Huang, Iain Cunningham, Igor Gitman, Ivan Moshkov, Jaehun Jung, Jan Kautz, Jane Polak Scowcroft, Jared Casper, Jian Zhang, Jiaqi Zeng, Jimmy Zhang, Jinze Xue, Jocelyn Huang, Joey Conway, John Kamalu, Jonathan M. Cohen, Joseph Jennings, Julien Veron Vialard, Junkeun Yi, Jupinder Parmar, Kari Briski, Katherine Cheung, Katherine Luna, Keith W. Ross, Keshav Santhanam, Kezhi Kong, Krzysztof Pawelec, Kumar Anik:
NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model. CoRR abs/2508.14444 (2025) - [i38]Yue Zhang, Jiaxin Zhang, Qiuyu Ren, Tahsin Saffat, Xiaoxuan Liu, Zitong Yang, Banghua Zhu, Yi Ma:
GAUSS: Benchmarking Structured Mathematical Skills for Large Language Models. CoRR abs/2509.18122 (2025) - [i37]Yifei Zuo, Yutong Yin, Zhichen Zeng, Ang Li, Banghua Zhu, Zhaoran Wang:
Local Linear Attention: An Optimal Interpolation of Linear and Softmax Attention For Test-Time Regression. CoRR abs/2510.01450 (2025) - [i36]Terry Yue Zhuo, Xiaolong Jin, Hange Liu, Juyong Jiang, Tianyang Liu, Chen Gong, Bhupesh Bishnoi, Vaisakhi Mishra, Marek Suppa, Noah Ziems, Saiteja Utpala, Ming Xu, Guangyu Song, Kaixin Li, Yuhan Cao, Bo Liu, Zheng Liu, Sabina Abdurakhmanova, Wenhao Yu, Mengzhao Jia, Jihan Yao, Kenneth Hamilton, Kumar Shridhar, Minh Chien Vu, Dingmin Wang, Jiawei Liu, Zijian Wang, Qian Liu, Binyuan Hui, Meg Risdal, Ahsen Khaliq, Atin Sood, Zhenchang Xing, Wasi Uddin Ahmad, John Grundy, David Lo, Banghua Zhu, Xiaoning Du, Torsten Scholak, Leandro von Werra:
BigCodeArena: Unveiling More Reliable Human Preferences in Code Generation via Execution. CoRR abs/2510.08697 (2025) - 2024
- [j6]Banghua Zhu
, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang:
Noisy Computing of the OR and MAX Functions. IEEE J. Sel. Areas Inf. Theory 5: 302-313 (2024) - [j5]Ziao Wang, Nadim Ghaddar, Banghua Zhu, Lele Wang:
Noisy Sorting Capacity. IEEE Trans. Inf. Theory 70(9): 6121-6138 (2024) - [c20]Cassidy Laidlaw, Banghua Zhu, Stuart Russell, Anca D. Dragan:
The Effective Horizon Explains Deep RL Performance in Stochastic Environments. ICLR 2024 - [c19]Qingyue Zhao, Banghua Zhu:
Towards the Fundamental Limits of Knowledge Transfer over Finite Domains. ICLR 2024 - [c18]Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Banghua Zhu, Hao Zhang, Michael I. Jordan, Joseph E. Gonzalez, Ion Stoica:
Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference. ICML 2024 - [c17]Banghua Zhu, Michael I. Jordan, Jiantao Jiao:
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF. ICML 2024 - [c16]Jinning Li, Xinyi Liu, Banghua Zhu, Jiantao Jiao, Masayoshi Tomizuka, Chen Tang, Wei Zhan:
Guided Online Distillation: Promoting Safe Reinforcement Learning by Offline Demonstration. ICRA 2024: 7447-7454 - [c15]Ying Sheng, Shiyi Cao, Dacheng Li, Coleman Hooper, Nicholas Lee, Shuo Yang, Christopher Chou, Banghua Zhu, Lianmin Zheng, Kurt Keutzer, Joseph Gonzalez, Ion Stoica:
SLoRA: Scalable Serving of Thousands of LoRA Adapters. MLSys 2024 - [c14]Ying Sheng, Shiyi Cao, Dacheng Li, Banghua Zhu, Zhuohan Li, Danyang Zhuo, Joseph E. Gonzalez, Ion Stoica:
Fairness in Serving Large Language Models. OSDI 2024: 965-988 - [i35]Ying Sheng, Shiyi Cao, Dacheng Li, Banghua Zhu, Zhuohan Li, Danyang Zhuo, Joseph E. Gonzalez, Ion Stoica:
Fairness in Serving Large Language Models. CoRR abs/2401.00588 (2024) - [i34]Banghua Zhu, Michael I. Jordan, Jiantao Jiao:
Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF. CoRR abs/2401.16335 (2024) - [i33]Hanlin Zhu, Banghua Zhu, Jiantao Jiao:
Efficient Prompt Caching via Embedding Similarity. CoRR abs/2402.01173 (2024) - [i32]Banghua Zhu, Norman Mu, Jiantao Jiao, David A. Wagner:
Generative AI Security: Challenges and Countermeasures. CoRR abs/2402.12617 (2024) - [i31]Wei-Lin Chiang, Lianmin Zheng, Ying Sheng, Anastasios Nikolas Angelopoulos, Tianle Li, Dacheng Li, Hao Zhang, Banghua Zhu, Michael I. Jordan, Joseph E. Gonzalez, Ion Stoica:
Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference. CoRR abs/2403.04132 (2024) - [i30]Ziao Wang, Nadim Ghaddar, Banghua Zhu, Lele Wang:
Noisy Computing of the Threshold Function. CoRR abs/2403.07227 (2024) - [i29]Tianle Li, Wei-Lin Chiang, Evan Frick, Lisa Dunlap, Tianhao Wu, Banghua Zhu, Joseph E. Gonzalez, Ion Stoica:
From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline. CoRR abs/2406.11939 (2024) - [i28]Jixuan Leng, Chengsong Huang, Banghua Zhu, Jiaxin Huang:
Taming Overconfidence in LLMs: Reward Calibration in RLHF. CoRR abs/2410.09724 (2024) - [i27]Evan Frick, Tianle Li, Connor Chen, Wei-Lin Chiang, Anastasios N. Angelopoulos, Jiantao Jiao, Banghua Zhu, Joseph E. Gonzalez, Ion Stoica:
How to Evaluate Reward Models for RLHF. CoRR abs/2410.14872 (2024) - 2023
- [c13]Banghua Zhu, Lun Wang, Qi Pang, Shuai Wang, Jiantao Jiao, Dawn Song, Michael I. Jordan:
Byzantine-Robust Federated Learning with Optimal Statistical Rates. AISTATS 2023: 3151-3178 - [c12]Ikechukwu Uchendu, Ted Xiao, Yao Lu, Banghua Zhu, Mengyuan Yan, Joséphine Simon, Matthew Bennice, Chuyuan Fu, Cong Ma, Jiantao Jiao, Sergey Levine, Karol Hausman:
Jump-Start Reinforcement Learning. ICML 2023: 34556-34583 - [c11]Geng Zhao, Banghua Zhu, Jiantao Jiao, Michael I. Jordan:
Online Learning in Stackelberg Games with an Omniscient Follower. ICML 2023: 42304-42316 - [c10]Banghua Zhu, Michael I. Jordan, Jiantao Jiao:
Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons. ICML 2023: 43037-43067 - [c9]Ziao Wang, Nadim Ghaddar, Banghua Zhu, Lele Wang:
Variable-Length Insertion-Based Noisy Sorting. ISIT 2023: 1782-1787 - [c8]Banghua Zhu, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang:
On the Optimal Bounds for Noisy Computing. ISIT 2023: 1788-1793 - [c7]Banghua Zhu, Ying Sheng, Lianmin Zheng, Clark W. Barrett, Michael I. Jordan, Jiantao Jiao:
Towards Optimal Caching and Model Selection for Large Model Inference. NeurIPS 2023 - [c6]Banghua Zhu, Mingyu Ding, Philip L. Jacobson, Ming Wu, Wei Zhan, Michael I. Jordan, Jiantao Jiao:
Doubly-Robust Self-Training. NeurIPS 2023 - [c5]Banghua Zhu, Stephen Bates, Zhuoran Yang, Yixin Wang, Jiantao Jiao, Michael I. Jordan:
The Sample Complexity of Online Contract Design. EC 2023: 1188 - [i26]Banghua Zhu, Jiantao Jiao, Michael I. Jordan:
Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons. CoRR abs/2301.11270 (2023) - [i25]Geng Zhao, Banghua Zhu, Jiantao Jiao, Michael I. Jordan:
Online Learning in Stackelberg Games with an Omniscient Follower. CoRR abs/2301.11518 (2023) - [i24]Banghua Zhu, Sai Praneeth Karimireddy, Jiantao Jiao, Michael I. Jordan:
Online Learning in a Creator Economy. CoRR abs/2305.11381 (2023) - [i23]Banghua Zhu, Mingyu Ding, Philip L. Jacobson, Ming Wu, Wei Zhan, Michael I. Jordan, Jiantao Jiao:
Doubly Robust Self-Training. CoRR abs/2306.00265 (2023) - [i22]Banghua Zhu, Ying Sheng, Lianmin Zheng, Clark W. Barrett, Michael I. Jordan, Jiantao Jiao:
On Optimal Caching and Model Multiplexing for Large Model Inference. CoRR abs/2306.02003 (2023) - [i21]Banghua Zhu, Hiteshi Sharma, Felipe Vieira Frujeri, Shi Dong, Chenguang Zhu, Michael I. Jordan, Jiantao Jiao:
Fine-Tuning Language Models with Advantage-Induced Policy Alignment. CoRR abs/2306.02231 (2023) - [i20]Banghua Zhu, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang:
On the Optimal Bounds for Noisy Computing. CoRR abs/2306.11951 (2023) - [i19]Banghua Zhu, Ziao Wang, Nadim Ghaddar, Jiantao Jiao, Lele Wang:
Noisy Computing of the OR and MAX Functions. CoRR abs/2309.03986 (2023) - [i18]Jinning Li, Xinyi Liu, Banghua Zhu, Jiantao Jiao, Masayoshi Tomizuka, Chen Tang, Wei Zhan:
Guided Online Distillation: Promoting Safe Reinforcement Learning by Offline Demonstration. CoRR abs/2309.09408 (2023) - [i17]Tianhao Wu, Banghua Zhu, Ruoyu Zhang, Zhaojin Wen, Kannan Ramchandran, Jiantao Jiao:
Pairwise Proximal Policy Optimization: Harnessing Relative Feedback for LLM Alignment. CoRR abs/2310.00212 (2023) - [i16]Zhikai Li, Xiaoxuan Liu, Banghua Zhu, Zhen Dong, Qingyi Gu, Kurt Keutzer:
QFT: Quantized Full-parameter Tuning of LLMs with Affordable Resources. CoRR abs/2310.07147 (2023) - [i15]Qingyue Zhao, Banghua Zhu:
Towards the Fundamental Limits of Knowledge Transfer over Finite Domains. CoRR abs/2310.07838 (2023) - [i14]Ying Sheng, Shiyi Cao, Dacheng Li, Coleman Hooper, Nicholas Lee, Shuo Yang, Christopher Chou, Banghua Zhu, Lianmin Zheng, Kurt Keutzer, Joseph E. Gonzalez, Ion Stoica:
S-LoRA: Serving Thousands of Concurrent LoRA Adapters. CoRR abs/2311.03285 (2023) - [i13]Baihe Huang, Banghua Zhu, Hanlin Zhu, Jason D. Lee, Jiantao Jiao, Michael I. Jordan:
Towards Optimal Statistical Watermarking. CoRR abs/2312.07930 (2023) - [i12]Cassidy Laidlaw, Banghua Zhu, Stuart Russell, Anca D. Dragan:
The Effective Horizon Explains Deep RL Performance in Stochastic Environments. CoRR abs/2312.08369 (2023) - 2022
- [j4]Cong Ma, Banghua Zhu, Jiantao Jiao, Martin J. Wainwright:
Minimax Off-Policy Evaluation for Multi-Armed Bandits. IEEE Trans. Inf. Theory 68(8): 5314-5339 (2022) - [j3]Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart Russell:
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. IEEE Trans. Inf. Theory 68(12): 8156-8196 (2022) - [c4]Banghua Zhu, Jiantao Jiao, Michael I. Jordan:
Robust Estimation for Non-parametric Families via Generative Adversarial Networks. ISIT 2022: 1100-1105 - [i11]Banghua Zhu, Jiantao Jiao, Michael I. Jordan:
Robust Estimation for Nonparametric Families via Generative Adversarial Networks. CoRR abs/2202.01269 (2022) - [i10]Ikechukwu Uchendu, Ted Xiao, Yao Lu, Banghua Zhu, Mengyuan Yan, Joséphine Simon, Matthew Bennice, Chuyuan Fu, Cong Ma, Jiantao Jiao, Sergey Levine, Karol Hausman:
Jump-Start Reinforcement Learning. CoRR abs/2204.02372 (2022) - [i9]Banghua Zhu, Lun Wang, Qi Pang, Shuai Wang, Jiantao Jiao, Dawn Song, Michael I. Jordan:
Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees. CoRR abs/2205.11765 (2022) - [i8]Banghua Zhu, Stephen Bates, Zhuoran Yang, Yixin Wang, Jiantao Jiao, Michael I. Jordan:
The Sample Complexity of Online Contract Design. CoRR abs/2211.05732 (2022) - 2021
- [c3]Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart Russell:
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. NeurIPS 2021: 11702-11716 - [i7]Matt Peng, Banghua Zhu, Jiantao Jiao:
Linear Representation Meta-Reinforcement Learning for Instant Adaptation. CoRR abs/2101.04750 (2021) - [i6]Cong Ma, Banghua Zhu, Jiantao Jiao, Martin J. Wainwright:
Minimax Off-Policy Evaluation for Multi-Armed Bandits. CoRR abs/2101.07781 (2021) - [i5]Paria Rashidinejad, Banghua Zhu, Cong Ma, Jiantao Jiao, Stuart Russell:
Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. CoRR abs/2103.12021 (2021) - 2020
- [j2]Banghua Zhu, Jiantao Jiao, David Tse:
Deconstructing Generative Adversarial Networks. IEEE Trans. Inf. Theory 66(11): 7155-7179 (2020) - [c2]Banghua Zhu, Jiantao Jiao, Jacob Steinhardt:
When does the Tukey Median work? ISIT 2020: 1201-1206 - [i4]Banghua Zhu, Jiantao Jiao, Jacob Steinhardt:
When does the Tukey median work? CoRR abs/2001.07805 (2020) - [i3]Banghua Zhu, Jiantao Jiao, Jacob Steinhardt:
Robust estimation via generalized quasi-gradients. CoRR abs/2005.14073 (2020)
2010 – 2019
- 2019
- [j1]Banghua Zhu, Jintao Wang, Longzhuang He, Jian Song:
Joint Transceiver Optimization for Wireless Communication PHY Using Neural Network. IEEE J. Sel. Areas Commun. 37(6): 1364-1373 (2019) - [i2]Banghua Zhu, Jiantao Jiao, David Tse:
Deconstructing Generative Adversarial Networks. CoRR abs/1901.09465 (2019) - [i1]Banghua Zhu, Jiantao Jiao, Jacob Steinhardt:
Generalized Resilience and Robust Statistics. CoRR abs/1909.08755 (2019) - 2017
- [c1]Abolfazl Hashemi, Banghua Zhu, Haris Vikalo:
Sparse Tensor Decomposition for Haplotype Assembly of Diploids and Polyploids. BCB 2017: 764-765
Coauthor Index
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