Publications

* denotes equal contribution.

2026

▸ Enterprise Sales Copilot: Enabling Real-Time AI Support with Automatic Information Retrieval in Live Sales Calls

Jielin Qiu, Liangwei Yang, Ming Zhu, Wenting Zhao, Zhiwei Liu, Juntao Tan, Zixiang Chen, Roshan Ram, Akshara Prabhakar, Rithesh Murthy, Shelby Heinecke, Caiming Xiong, Silvio Savarese, Huan Wang. Preprint, 2026.

▸ BehaviorBench: Modeling Real-World User Decisions from Behavioral Traces

Liangwei Yang, Jielin Qiu, Zixiang Chen, Ming Zhu, Juntao Tan, Zhiwei Liu, Wenting Zhao, Zhujun Lan, Akshara Prabhakar, Silvio Savarese, Huan Wang, Shelby Heinecke. Preprint, 2026.

▸ Whisper-AuT: Domain-Adapted Audio Encoder for Efficient Audio-LLM Training

Jielin Qiu, Ming Zhu, Wenting Zhao, Zhiwei Liu, Liangwei Yang, Zixiang Chen, Roshan Ram, Akshara Prabhakar, Juntao Tan, Rithesh Murthy, Shelby Heinecke, Caiming Xiong, Silvio Savarese, Huan Wang. Preprint, 2026.

▸ Building Enterprise Realtime Voice Agents from Scratch: A Technical Tutorial

Jielin Qiu, Zixiang Chen, Liangwei Yang, Ming Zhu, Zhiwei Liu, Juntao Tan, Wenting Zhao, Rithesh Murthy, Roshan Ram, Akshara Prabhakar, Shelby Heinecke, Caiming Xiong, Silvio Savarese, Huan Wang. Preprint, 2026.

▸ VoiceAgentRAG: Solving the RAG Latency Bottleneck in Real-Time Voice Agents Using Dual-Agent Architectures

Jielin Qiu, Jianguo Zhang, Zixiang Chen, Liangwei Yang, Ming Zhu, Juntao Tan, Haolin Chen, Wenting Zhao, Rithesh Murthy, Roshan Ram, Akshara Prabhakar, Shelby Heinecke, Caiming Xiong, Silvio Savarese, Huan Wang. Preprint, 2026.

▸ AudioCapBench: Quick Evaluation on Audio Captioning across Sound, Music, and Speech

Jielin Qiu, Jianguo Zhang, Zixiang Chen, Liangwei Yang, Ming Zhu, Juntao Tan, Haolin Chen, Wenting Zhao, Rithesh Murthy, Roshan Ram, Akshara Prabhakar, Shelby Heinecke, Caiming Xiong, Silvio Savarese, Huan Wang. Preprint, 2026.

▸ Position: Vector Prompt Interfaces Should Be Exposed to Enable Customization of Large Language Models

Liangwei Yang, Shiyu Wang, Haolin Chen, Rithesh Murthy, Ming Zhu, Jielin Qiu, Zixiang Chen, Juntao Tan, Jianguo Zhang, Zhiwei Liu, Wenting Zhao, Silvio Savarese, Caiming Xiong, Huan Wang, Shelby Heinecke, ICML 2026.

▸ Prompt Optimization Via Diffusion Language Models

Shiyu Wang, Haolin Chen, Liangwei Yang, Jielin Qiu, Rithesh Murthy, Ming Zhu, Zixiang Chen, Silvio Savarese, Caiming Xiong, Shelby Heinecke, Huan Wang, arXiv:2602.18449, 2026.

2025

▸ Group Representational Position Encoding

Yifan Zhang, Zixiang Chen, Yifeng Liu, Zhen Qin, Huizhuo Yuan, Kangping Xu, Yang Yuan, Quanquan Gu, Andrew Chi-Chih Yao. Preprint, 2025.

▸ LoCoBench-Agent: An Interactive Benchmark for LLM Agents in Long-Context Software Engineering

Jielin Qiu, Zuxin Liu, Zhiwei Liu, Rithesh Murthy, Jianguo Zhang, Haolin Chen, Shiyu Wang, Ming Zhu, Liangwei Yang, Juntao Tan, Roshan Ram, Akshara Prabhakar, Tulika Awalgaonkar, Zixiang Chen, Zhepeng Cen, Cheng Qian, Shelby Heinecke, Weiran Yao, Silvio Savarese, Caiming Xiong, Huan Wang. Preprint, 2025.

▸ On the Power of Multitask Representation Learning with Gradient Descent

Qiaobo Li, Zixiang Chen, Yihe Deng, Yiwen Kou, Yuan Cao, Quanquan Gu. AISTATS 2025.

▸ Enterprise Deep Research: Steerable Multi-Agent Deep Research for Enterprise Analytics

Akshara Prabhakar, Roshan Ram, Zixiang Chen, Silvio Savarese, Frank Wang, Caiming Xiong, Huan Wang, Weiran Yao, arXiv:2510.17797, 2025.

▸ Global Convergence and Rich Feature Learning in L-Layer Infinite-Width Neural Networks under μP Parametrization 

Zixiang Chen*, Greg Yang*, Qingyue Zhao, Quanquan Gu, ICML 2025.

▸ Guided Discrete Diffusion for Electronic Health Record Generation

Jun Han*, Zixiang Chen*, Yongqian Li, Yiwen Kou, Eran Halperin, Robert E. Tillman, Quanquan Gu, TMLR 2025.

▸ Convergence of Score-Based Discrete Diffusion Models: A Discrete-Time Analysis

Zikun Zhang, Zixiang Chen, Quanquan Gu, ICLR 2025.

2024

▸ Fast Sampling via Discrete Non-Markov Diffusion Models

Zixiang Chen, Huizhuo Yuan, Yongqian Li, Yiwen Kou, Junkai Zhang, Quanquan Gu, NeurIPS 2024.

▸ Self-Play Fine-Tuning of Diffusion Models for Text-to-Image Generation

Huizhuo Yuan*, Zixiang Chen*, Kaixuan Ji*, Quanquan Gu, NeurIPS 2024.

▸ Matching the Statistical Query Lower Bound for k-sparse Parity Problems with Stochastic Gradient Descent

Yiwen Kou*, Zixiang Chen*, Quanquan Gu, Sham M. Kakade, NeurIPS 2024.

▸ Self-Play Fine-Tuning Converts Weak Language Models to Strong Language Models

Zixiang Chen*, Yihe Deng*, Huizhuo Yuan*, Kaixuan Ji and Quanquan Gu, ICML 2024.

▸ Understanding Transferable Representation Learning and Zero-shot Transfer in CLIP

Zixiang Chen*, Yihe Deng*, Yuanzhi Li, and Quanquan Gu, In Proc. of the 12th International Conference on Learning Representations (ICLR), Vienna, Austria, 2024.

▸ How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression?

Jingfeng Wu, Difan Zou, Zixiang Chen, Vladimir Braverman, Quanquan Gu, Peter L. Bartlett, In Proc. of the 12th International Conference on Learning Representations (ICLR), Vienna, Austria, 2024. (Spotlight)

2023

▸ Fast Sampling via De-randomization for Discrete Diffusion Models

Zixiang Chen, Huizhuo Yuan, Yongqian Li, Junkai Zhang, Yiwen Kou, Quanquan Gu, NeurIPS 2023 Workshop on Diffusion Models.

▸ Rephrase and Respond: Let Large Language Models Ask Better Questions for Themselves

Yihe Deng, Weitong Zhang, Zixiang Chen and Quanquan Gu, arXiv:2311.04205, 2023.

▸ Implicit Bias of Gradient Descent for Two-layer ReLU and Leaky ReLU Networks

Yiwen Kou*, Zixiang Chen* and Quanquan Gu In Proc. of Advances in Neural Information Processing Systems (NeurIPS) 36, New Orleans, LA, USA, 2023.

▸ Why Does Sharpness-Aware Minimization Generalize Better Than SGD?

Zixiang Chen*, Junkai Zhang*, Yiwen Kou, Xiangning Chen, Cho-Jui Hsieh and Quanquan Gu In Proc. of Advances in Neural Information Processing Systems (NeurIPS) 36, New Orleans, LA, USA, 2023.

▸ Benign Overfitting for Two-layer ReLU Networks

Yiwen Kou*, Zixiang Chen*, Yuanzhou Chen and Quanquan Gu, In Proc. of the 40th International Conference on Machine Learning (ICML), Hawaii, USA, 2023.

▸ Finite-Sample Analysis of Learning High-Dimensional Single ReLU Neuron

Jingfeng Wu*, Difan Zou*, Zixiang Chen*, Vladimir Braverman, Quanquan Gu and Sham M. Kakade, In Proc. of the 40th International Conference on Machine Learning (ICML), Hawaii, USA, 2023.

▸ A General Framework for Sample-Efficient Function Approximation in Reinforcement Learning

Zixiang Chen*, Chris Junchi Li*, Huizhuo Yuan*, Quanquan Gu, Michael I. Jordan, In Proc. of the 11th International Conference on Learning Representations (ICLR), 2023. (Spotlight)

▸ How Does Semi-supervised Learning with Pseudo-labelers Work? A Case Study

Yiwen Kou, Zixiang Chen, Yuan Cao and Quanquan Gu, In Proc. of the 11th International Conference on Learning Representations (ICLR), 2023.

▸ Understanding Train-Validation Split in Meta-Learning with Neural Networks

Xinzhe Zuo, Zixiang Chen, Huaxiu Yao, Yuan Cao and Quanquan Gu, In Proc. of the 11th International Conference on Learning Representations (ICLR), 2023.

2022

▸ Towards Understanding Mixture of Experts in Deep Learning

Zixiang Chen, Yihe Deng, Yue Wu, Quanquan Gu, Yuanzhi Li, Advances in Neural Information Processing Systems (NeurIPS), 2022.

▸ Benign Overfitting in Two-layer Convolutional Neural Networks

Yuan Cao*, Zixiang Chen*, Mikhail Belkin, Quanquan Gu, Advances in Neural Information Processing Systems (NeurIPS), 2022. (Oral)

▸ Almost Optimal Algorithms for Two-player Zero-Sum Linear Mixture Markov Games

Zixiang Chen, Dongruo Zhou and Quanquan Gu, In Proc. of the 33rd International Conference on Algorithmic Learning Theory (ALT), 2022.

▸ Faster Perturbed Stochastic Gradient Methods for Finding Local Minima

Zixiang Chen*, Dongruo Zhou* and Quanquan Gu, In Proc. of the 33rd International Conference on Algorithmic Learning Theory (ALT), 2022.

▸ Self-training Converts Weak Learners to Strong Learners in Mixture Models

Spencer Frei*, Difan Zou*, Zixiang Chen* and Quanquan Gu, In Proc. of the 23rd International Conference on Artificial Intelligence and Statistics, 2022.

2021

▸ How Much Over-parameterization Is Sufficient to Learn Deep ReLU Networks?

Zixiang Chen*, Yuan Cao*, Difan Zou* and Quanquan Gu, In Proc. of the 9th International Conference on Learning Representations (ICLR), 2021.

2020

▸ A Generalized Neural Tangent Kernel Analysis for Two-layer Neural Networks

Zixiang Chen, Yuan Cao, Quanquan Gu and Tong Zhang, Advances in Neural Information Processing Systems (NeurIPS), 2020.

2018

▸ Stein Neural Sampler

Tianyang Hu*, Zixiang Chen*, Hanxi Sun*, Jincheng Bai, Mao Ye, Guang Cheng. Preprint, 2018.

Open Source

▸ SPIN — https://github.com/uclaml/SPIN

▸ Enterprise Deep Research — https://github.com/SalesforceAIResearch/enterprise-deep-research