Sparse Tensor Decomposition for Haplotype Assembly of Diploids and Polyploids. - Abolfazl Hashemi; Banghua Zhu; Haris Vikalo (BCB, 2017)

Generalized Resilience and Robust Statistics. - Banghua Zhu; Jiantao Jiao; Jacob Steinhardt (CoRR, 2019)

Joint Transceiver Optimization for Wireless Communication PHY Using Neural Network. - Banghua Zhu; Jintao Wang 001; Longzhuang He; Jian Song 004 (IEEE J. Sel. Areas Commun., 2019)

When does the Tukey Median work? - Banghua Zhu; Jiantao Jiao; Jacob Steinhardt (ISIT, 2020)

Robust estimation via generalized quasi-gradients. - Banghua Zhu; Jiantao Jiao; Jacob Steinhardt (CoRR, 2020)

Deconstructing Generative Adversarial Networks. - Banghua Zhu; Jiantao Jiao; David Tse (IEEE Trans. Inf. Theory, 2020)

Bridging Offline Reinforcement Learning and Imitation Learning: A Tale of Pessimism. - Paria Rashidinejad; Banghua Zhu; Cong Ma 001; Jiantao Jiao; Stuart Russell 001 (NeurIPS, 2021)

Linear Representation Meta-Reinforcement Learning for Instant Adaptation. - Matt Peng; Banghua Zhu; Jiantao Jiao (CoRR, 2021)

Robust Estimation for Non-parametric Families via Generative Adversarial Networks. - Banghua Zhu; Jiantao Jiao; Michael I. Jordan (ISIT, 2022)

Robust Estimation for Nonparametric Families via Generative Adversarial Networks. - Banghua Zhu; Jiantao Jiao; Michael I. Jordan (CoRR, 2022)

Byzantine-Robust Federated Learning with Optimal Statistical Rates and Privacy Guarantees. - Banghua Zhu; Lun Wang 001; Qi Pang; Shuai Wang 011; Jiantao Jiao; Dawn Song; Michael I. Jordan (CoRR, 2022)

Minimax Off-Policy Evaluation for Multi-Armed Bandits. - Cong Ma 001; Banghua Zhu; Jiantao Jiao; Martin J. Wainwright (IEEE Trans. Inf. Theory, 2022)

Byzantine-Robust Federated Learning with Optimal Statistical Rates. - Banghua Zhu; Lun Wang 001; Qi Pang; Shuai Wang 011; Jiantao Jiao; Dawn Song; Michael I. Jordan (AISTATS, 2023)

Jump-Start Reinforcement Learning. - Ikechukwu Uchendu; Ted Xiao; Yao Lu 006; Banghua Zhu; Mengyuan Yan; Joséphine Simon; Matthew Bennice; Chuyuan Fu; Cong Ma 001; Jiantao Jiao; Sergey Levine; Karol Hausman (ICML, 2023)

Online Learning in Stackelberg Games with an Omniscient Follower. - Geng Zhao; Banghua Zhu; Jiantao Jiao; Michael I. Jordan (ICML, 2023)

Principled Reinforcement Learning with Human Feedback from Pairwise or K-wise Comparisons. - Banghua Zhu; Michael I. Jordan; Jiantao Jiao (ICML, 2023)

Variable-Length Insertion-Based Noisy Sorting. - Ziao Wang; Nadim Ghaddar; Banghua Zhu; Lele Wang 001 (ISIT, 2023)

On the Optimal Bounds for Noisy Computing. - Banghua Zhu; Ziao Wang; Nadim Ghaddar; Jiantao Jiao; Lele Wang 001 (ISIT, 2023)

Towards Optimal Caching and Model Selection for Large Model Inference. - Banghua Zhu; Ying Sheng 007; Lianmin Zheng; Clark W. Barrett; Michael I. Jordan; Jiantao Jiao (NeurIPS, 2023)

Doubly-Robust Self-Training. - Banghua Zhu; Mingyu Ding; Philip L. Jacobson; Ming Wu; Wei Zhan; Michael I. Jordan; Jiantao Jiao (NeurIPS, 2023)

The Sample Complexity of Online Contract Design. - Banghua Zhu; Stephen Bates; Zhuoran Yang; Yixin Wang 002; Jiantao Jiao; Michael I. Jordan (EC, 2023)

Online Learning in a Creator Economy. - Banghua Zhu; Sai Praneeth Karimireddy; Jiantao Jiao; Michael I. Jordan (CoRR, 2023)

On Optimal Caching and Model Multiplexing for Large Model Inference. - Banghua Zhu; Ying Sheng 007; Lianmin Zheng; Clark W. Barrett; Michael I. Jordan; Jiantao Jiao (CoRR, 2023)

Fine-Tuning Language Models with Advantage-Induced Policy Alignment. - Banghua Zhu; Hiteshi Sharma; Felipe Vieira Frujeri; Shi Dong; Chenguang Zhu; Michael I. Jordan; Jiantao Jiao (CoRR, 2023)

Pairwise Proximal Policy Optimization: Harnessing Relative Feedback for LLM Alignment. - Tianhao Wu 002; Banghua Zhu; Ruoyu Zhang; Zhaojin Wen; Kannan Ramchandran; Jiantao Jiao (CoRR, 2023)

QFT: Quantized Full-parameter Tuning of LLMs with Affordable Resources. - Zhikai Li; Xiaoxuan Liu; Banghua Zhu; Zhen Dong 003; Qingyi Gu; Kurt Keutzer (CoRR, 2023)

S-LoRA: Serving Thousands of Concurrent LoRA Adapters. - Ying Sheng 007; Shiyi Cao; Dacheng Li; Coleman Hooper; Nicholas Lee; Shuo Yang; Christopher Chou; Banghua Zhu; Lianmin Zheng; Kurt Keutzer; Joseph E. Gonzalez; Ion Stoica (CoRR, 2023)

Towards Optimal Statistical Watermarking. - Baihe Huang; Banghua Zhu; Hanlin Zhu; Jason D. Lee; Jiantao Jiao; Michael I. Jordan (CoRR, 2023)

The Effective Horizon Explains Deep RL Performance in Stochastic Environments. - Cassidy Laidlaw; Banghua Zhu; Stuart Russell 001; Anca D. Dragan (ICLR, 2024)

Towards the Fundamental Limits of Knowledge Transfer over Finite Domains. - Qingyue Zhao 001; Banghua Zhu (ICLR, 2024)

Chatbot Arena: An Open Platform for Evaluating LLMs by Human Preference. - Wei-Lin Chiang; Lianmin Zheng; Ying Sheng 007; Anastasios Nikolas Angelopoulos; Tianle Li; Dacheng Li; Banghua Zhu; Hao Zhang 025; Michael I. Jordan; Joseph E. Gonzalez; Ion Stoica (ICML, 2024)

Iterative Data Smoothing: Mitigating Reward Overfitting and Overoptimization in RLHF. - Banghua Zhu; Michael I. Jordan; Jiantao Jiao (ICML, 2024)

Guided Online Distillation: Promoting Safe Reinforcement Learning by Offline Demonstration. - Jinning Li 002; Xinyi Liu; Banghua Zhu; Jiantao Jiao; Masayoshi Tomizuka; Chen Tang 001; Wei Zhan (ICRA, 2024)

SLoRA: Scalable Serving of Thousands of LoRA Adapters. - Ying Sheng 007; Shiyi Cao; Dacheng Li; Coleman Hooper; Nicholas Lee; Shuo Yang; Christopher Chou; Banghua Zhu; Lianmin Zheng; Kurt Keutzer; Joseph Gonzalez 001; Ion Stoica (MLSys, 2024)

Fairness in Serving Large Language Models. - Ying Sheng 007; Shiyi Cao; Dacheng Li; Banghua Zhu; Zhuohan Li 001; Danyang Zhuo; Joseph E. Gonzalez; Ion Stoica (OSDI, 2024)

Efficient Prompt Caching via Embedding Similarity. - Hanlin Zhu; Banghua Zhu; Jiantao Jiao (CoRR, 2024)

Generative AI Security: Challenges and Countermeasures. - Banghua Zhu; Norman Mu; Jiantao Jiao; David A. Wagner 001 (CoRR, 2024)

From Crowdsourced Data to High-Quality Benchmarks: Arena-Hard and BenchBuilder Pipeline. - Tianle Li; Wei-Lin Chiang; Evan Frick; Lisa Dunlap; Tianhao Wu 002; Banghua Zhu; Joseph E. Gonzalez; Ion Stoica (CoRR, 2024)

Noisy Computing of the OR and MAX Functions. - Banghua Zhu; Ziao Wang; Nadim Ghaddar; Jiantao Jiao; Lele Wang 001 (IEEE J. Sel. Areas Inf. Theory, 2024)

Noisy Sorting Capacity. - Ziao Wang; Nadim Ghaddar; Banghua Zhu; Lele Wang 001 (IEEE Trans. Inf. Theory, 2024)

Noisy Computing of the Threshold Function. - Ziao Wang; Nadim Ghaddar; Banghua Zhu; Lele Wang 001 (ALT, 2025)

How to Evaluate Reward Models for RLHF. - Evan Frick; Tianle Li; Connor Chen; Wei-Lin Chiang; Anastasios Nikolas Angelopoulos; Jiantao Jiao; Banghua Zhu; Joseph E. Gonzalez; Ion Stoica (ICLR, 2025)

Taming Overconfidence in LLMs: Reward Calibration in RLHF. - Jixuan Leng; Chengsong Huang; Banghua Zhu; Jiaxin Huang 001 (ICLR, 2025)

MMMG: a Comprehensive and Reliable Evaluation Suite for Multitask Multimodal Generation. - Jihan Yao; Yushi Hu; Yujie Yi; Bin Han 011; Shangbin Feng; Guang Yang 046; Bingbing Wen; Ranjay Krishna; Lucy Lu Wang; Yulia Tsvetkov; Noah A. Smith; Banghua Zhu (CoRR, 2025)

Beyond Ten Turns: Unlocking Long-Horizon Agentic Search with Large-Scale Asynchronous RL. - Jiaxuan Gao; Wei Fu; Minyang Xie; Shusheng Xu; Chuyi He; Zhiyu Mei; Banghua Zhu; Yi Wu 013 (CoRR, 2025)

NVIDIA Nemotron Nano 2: An Accurate and Efficient Hybrid Mamba-Transformer Reasoning Model. - Aarti Basant; Abhijit Khairnar; Abhijit Paithankar; Abhinav Khattar; Adithya Renduchintala; Aditya Malte; Akhiad Bercovich; Akshay Hazare; Alejandra Rico; Aleksander Ficek; Alex Kondratenko; Alex Shaposhnikov; et al. (CoRR, 2025)

GAUSS: Benchmarking Structured Mathematical Skills for Large Language Models. - Yue Zhang; Jiaxin Zhang; Qiuyu Ren; Tahsin Saffat; Xiaoxuan Liu; Zitong Yang; Banghua Zhu; Yi Ma (CoRR, 2025)

Local Linear Attention: An Optimal Interpolation of Linear and Softmax Attention For Test-Time Regression. - Yifei Zuo; Yutong Yin; Zhichen Zeng; Ang Li; Banghua Zhu; Zhaoran Wang 001 (CoRR, 2025)

BigCodeArena: Unveiling More Reliable Human Preferences in Code Generation via Execution. - Terry Yue Zhuo; Xiaolong Jin; Hange Liu; Juyong Jiang; Tianyang Liu 003; Chen Gong 005; Bhupesh Bishnoi; Vaisakhi Mishra; Marek Suppa; Noah Ziems; Saiteja Utpala; Ming Xu; et al. (CoRR, 2025)