Lin, Zinan

34 publications

ICLRW 2025 Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model Zinan Lin, Tadas Baltrusaitis, Sergey Yekhanin

ICLR 2025 Distilled Decoding 1: One-Step Sampling of Image Auto-Regressive Models with Flow Matching Enshu Liu, Xuefei Ning, Yu Wang, Zinan Lin

NeurIPS 2025 Distilled Decoding 2: One-Step Sampling of Image Auto-Regressive Models with Conditional Score Distillation Enshu Liu, Qian Chen, Xuefei Ning, Shengen Yan, Guohao Dai, Zinan Lin, Yu Wang

NeurIPS 2025 Latent Zoning Network: A Unified Principle for Generative Modeling, Representation Learning, and Classification Zinan Lin, Enshu Liu, Xuefei Ning, Junyi Zhu, Wenyu Wang, Sergey Yekhanin

ICLR 2025 Linear Combination of Saved Checkpoints Makes Consistency and Diffusion Models Better Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Shuaiqi Wang, Matthew B. Blaschko, Sergey Yekhanin, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang

ICLR 2025 MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models Chejian Xu, Jiawei Zhang, Zhaorun Chen, Chulin Xie, Mintong Kang, Yujin Potter, Zhun Wang, Zhuowen Yuan, Alexander Xiong, Zidi Xiong, Chenhui Zhang, Lingzhi Yuan, Yi Zeng, Peiyang Xu, Chengquan Guo, Andy Zhou, Jeffrey Ziwei Tan, Xuandong Zhao, Francesco Pinto, Zhen Xiang, Yu Gai, Zinan Lin, Dan Hendrycks, Bo Li, Dawn Song

NeurIPS 2025 Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Shuaiqi Wang, Vikas Raunak, Arturs Backurs, Victor Reis, Pei Zhou, Sihao Chen, Longqi Yang, Zinan Lin, Sergey Yekhanin, Giulia Fanti

NeurIPS 2025 Synthesize Privacy-Preserving High-Resolution Images via Private Textual Intermediaries Haoxiang Wang, Zinan Lin, Da Yu, Huishuai Zhang

ICLR 2025 ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation Tianchen Zhao, Tongcheng Fang, Haofeng Huang, Rui Wan, Widyadewi Soedarmadji, Enshu Liu, Shiyao Li, Zinan Lin, Guohao Dai, Shengen Yan, Huazhong Yang, Xuefei Ning, Yu Wang

NeurIPS 2024 Can LLMs Learn by Teaching for Better Reasoning? a Preliminary Study Xuefei Ning, Zifu Wang, Shiyao Li, Zinan Lin, Peiran Yao, Tianyu Fu, Matthew B. Blaschko, Guohao Dai, Huazhong Yang, Yu Wang

ICLR 2024 Differentially Private Synthetic Data via Foundation Model APIs 1: Images Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Harsha Nori, Sergey Yekhanin

ICML 2024 Differentially Private Synthetic Data via Foundation Model APIs 2: Text Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin A Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin

ICLRW 2024 Differentially Private Synthetic Data via Foundation Model APIs 2: Text Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin A Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin

ICLR 2024 Efficiently Computing Similarities to Private Datasets Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski

CVPR 2024 FlashEval: Towards Fast and Accurate Evaluation of Text-to-Image Diffusion Generative Models Lin Zhao, Tianchen Zhao, Zinan Lin, Xuefei Ning, Guohao Dai, Huazhong Yang, Yu Wang

NeurIPS 2024 Improving the Training of Rectified Flows Sangyun Lee, Zinan Lin, Giulia Fanti

ECCV 2024 MixDQ: Memory-Efficient Few-Step Text-to-Image Diffusion Models with Metric-Decoupled Mixed Precision Quantization Tianchen Zhao, Xuefei Ning, Tongcheng Fang, Enshu Liu, Guyue Huang, Zinan Lin, Shengen Yan, Guohao Dai, Yu Wang

AISTATS 2024 Mixture-of-Linear-Experts for Long-Term Time Series Forecasting Ronghao Ni, Zinan Lin, Shuaiqi Wang, Giulia Fanti

ICLR 2024 Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation Xinyu Tang, Richard Shin, Huseyin A Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Robert Sim

NeurIPS 2024 RedCode: Risky Code Execution and Generation Benchmark for Code Agents Chengquan Guo, Xun Liu, Chulin Xie, Andy Zhou, Yi Zeng, Zinan Lin, Dawn Song, Bo Li

TMLR 2024 Selective Pre-Training for Private Fine-Tuning Da Yu, Sivakanth Gopi, Janardhan Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang

ICLR 2024 Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation Xuefei Ning, Zinan Lin, Zixuan Zhou, Zifu Wang, Huazhong Yang, Yu Wang

NeurIPS 2023 DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models Boxin Wang, Weixin Chen, Hengzhi Pei, Chulin Xie, Mintong Kang, Chenhui Zhang, Chejian Xu, Zidi Xiong, Ritik Dutta, Rylan Schaeffer, Sang Truong, Simran Arora, Mantas Mazeika, Dan Hendrycks, Zinan Lin, Yu Cheng, Sanmi Koyejo, Dawn Song, Bo Li

NeurIPSW 2023 Differentially Private Synthetic Data via Foundation Model APIs 1: Images Zinan Lin, Sivakanth Gopi, Janardhan Kulkarni, Harsha Nori, Sergey Yekhanin

ICML 2023 OMS-DPM: Optimizing the Model Schedule for Diffusion Probabilistic Models Enshu Liu, Xuefei Ning, Zinan Lin, Huazhong Yang, Yu Wang

NeurIPSW 2023 Training Private and Efficient Language Models with Synthetic Data from LLMs Da Yu, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Janardhan Kulkarni, Zinan Lin, Chulin Xie, Huishuai Zhang, Wanrong Zhang

NeurIPSW 2022 Distributional Privacy for Data Sharing Zinan Lin, Shuaiqi Wang, Vyas Sekar, Giulia Fanti

AAAI 2022 RareGAN: Generating Samples for Rare Classes Zinan Lin, Hao Liang, Giulia Fanti, Vyas Sekar

AISTATS 2021 On the Privacy Properties of GAN-Generated Samples Zinan Lin, Vyas Sekar, Giulia Fanti

ICML 2021 Pareto GAN: Extending the Representational Power of GANs to Heavy-Tailed Distributions Todd Huster, Jeremy Cohen, Zinan Lin, Kevin Chan, Charles Kamhoua, Nandi O. Leslie, Cho-Yu Jason Chiang, Vyas Sekar

NeurIPS 2021 Why Spectral Normalization Stabilizes GANs: Analysis and Improvements Zinan Lin, Vyas Sekar, Giulia Fanti

ICML 2020 InfoGAN-CR and ModelCentrality: Self-Supervised Model Training and Selection for Disentangling GANs Zinan Lin, Kiran Thekumparampil, Giulia Fanti, Sewoong Oh

NeurIPS 2018 PacGAN: The Power of Two Samples in Generative Adversarial Networks Zinan Lin, Ashish Khetan, Giulia Fanti, Sewoong Oh

NeurIPS 2018 Robustness of Conditional GANs to Noisy Labels Kiran K Thekumparampil, Ashish Khetan, Zinan Lin, Sewoong Oh