DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis
Chen Gong, Kecen Li, Zinan Lin, Tianhao Wang
CCS 2025 | July 2025
Zinan Lin
Senior Researcher
Papiers de Collaboration
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Scaling Textual Gradients via Sampling-Based Momentum
Zixin Ding, Junyuan Hong, Jiachen T. Wang, Zinan Lin, Zhangyang Wang, Yuxin Chen
ICML 2025 Workshop on Test-Time Adaptation | June 2025
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Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Models
Zinan Lin, Tadas Baltrusaitis, Sergey Yekhanin
February 2025
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Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching
Enshu Liu, Xuefei Ning, Yu Wang, Zinan Lin
ICLR 2025 | February 2025
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Inferentially-Private Private Information
Shuaiqi Wang, Shuran Zheng, Zinan Lin, Giulia Fanti, Zhiwei Steven Wu
WWW 2025 | February 2025
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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 | February 2025
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MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models
Chejian Xu, Jiawei Zhang, Zhaorun Chen, Chulin Xie, Mintong Kang, Zhuowen Yuan, Zidi Xiong, Chenhui Zhang, Lingzhi Yuan, Yi Zeng, Peiyang Xu, Chengquan Guo, Andy Zhou, Jeffrey Ziwei Tan, Zhun Wang, Alexander Xiong, Xuandong Zhao, Yu Gai, Francesco Pinto, Yujin Potter, Zhen Xiang, Zinan Lin, Dan Hendrycks, Dawn Song, Bo Li
ICLR 2025 | February 2025
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ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation
Tianchen Zhao, Tongcheng Fang, Enshu Liu, Wan Rui, Widyadewi Soedarmadji, Shiyao Li, Zinan Lin, Guohao Dai, Shengen Yan, Huazhong Yang, Xuefei Ning
ICLR 2025 | February 2025
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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
NeurIPS 2024 | October 2024
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Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin
ICML 2024 | July 2024
Spotlight
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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
ECCV 2024 | July 2024
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Statistic Maximal Leakage
Shuaiqi Wang, Zinan Lin, Giulia Fanti
IEEE International Symposium on Information Theory 2024 | July 2024
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Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs
Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Matthew B. Blaschko, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang
June 2024
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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
NeurIPS 2024 | June 2024
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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
CVPR 2024 | June 2024
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Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
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Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
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Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation
Xuefei Ning, Zinan Lin, Zixuan Zhou, Zifu Wang, Huazhong Yang, Yu Wang
ICLR 2024 | May 2024
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Mixture-of-Linear-Experts for Long-term Time Series Forecasting
Ronghao Ni, Zinan Lin, Shuaiqi Wang, Giulia Fanti
AISTATS 2024 | May 2024
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Efficiently Computing Similarities to Private Datasets
Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski
ICLR 2024 | May 2024
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Improving the Training of Rectified Flows
Sangyun Lee, Zinan Lin, Giulia Fanti
NeurIPS 2024 | May 2024
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Rescaling Intermediate Features Makes Trained Consistency Models Perform Better
Junyi Zhu, Zinan Lin, Enshu Liu, Xuefei Ning, Matthew B. Blaschko
ICLR (TinyPapers) 2024 | May 2024
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Selective Pre-training for Private Fine-tuning
Da Yu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang
TMLR | May 2024
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Summary Statistic Privacy in Data Sharing
Zinan Lin, Shuaiqi Wang, Vyas Sekar, Giulia Fanti
IEEE Journal on Selected Areas in Information Theory | March 2024
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Training Private and Efficient Language Models with Synthetic Data from LLMs
Da Yu, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Janardhan (Jana) Kulkarni, Zinan Lin, Chulin Xie, Huishuai Zhang, Wanrong Zhang
NeurIPS 2023 SoLaR Workshop | December 2023
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OMS-DPM: Optimizing the Model Schedule for Diffusion Probabilistic Models
Enshu Liu, Xuefei Ning, Zinan Lin, Huazhong Yang, Yu Wang
ICML 2023 | July 2023
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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 T. Truong, Simran Arora, Mantas Mazeika, Dan Hendrycks, Zinan Lin, Yu Cheng, Sanmi Koyejo, Dawn Song, Bo Li
NeurIPS 2023 | June 2023
Outstanding Paper Award
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DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis
Chen Gong, Kecen Li, Zinan Lin, Tianhao Wang
CCS 2025 | July 2025
-
Scaling Textual Gradients via Sampling-Based Momentum
Zixin Ding, Junyuan Hong, Jiachen T. Wang, Zinan Lin, Zhangyang Wang, Yuxin Chen
ICML 2025 Workshop on Test-Time Adaptation | June 2025
-
Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Models
Zinan Lin, Tadas Baltrusaitis, Sergey Yekhanin
February 2025
-
Inferentially-Private Private Information
Shuaiqi Wang, Shuran Zheng, Zinan Lin, Giulia Fanti, Zhiwei Steven Wu
WWW 2025 | February 2025
-
ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation
Tianchen Zhao, Tongcheng Fang, Enshu Liu, Wan Rui, Widyadewi Soedarmadji, Shiyao Li, Zinan Lin, Guohao Dai, Shengen Yan, Huazhong Yang, Xuefei Ning
ICLR 2025 | February 2025
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MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models
Chejian Xu, Jiawei Zhang, Zhaorun Chen, Chulin Xie, Mintong Kang, Zhuowen Yuan, Zidi Xiong, Chenhui Zhang, Lingzhi Yuan, Yi Zeng, Peiyang Xu, Chengquan Guo, Andy Zhou, Jeffrey Ziwei Tan, Zhun Wang, Alexander Xiong, Xuandong Zhao, Yu Gai, Francesco Pinto, Yujin Potter, Zhen Xiang, Zinan Lin, Dan Hendrycks, Dawn Song, Bo Li
ICLR 2025 | February 2025
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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 | February 2025
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Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching
Enshu Liu, Xuefei Ning, Yu Wang, Zinan Lin
ICLR 2025 | February 2025
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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
NeurIPS 2024 | October 2024
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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
ECCV 2024 | July 2024
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Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin
ICML 2024 | July 2024
Spotlight
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Statistic Maximal Leakage
Shuaiqi Wang, Zinan Lin, Giulia Fanti
IEEE International Symposium on Information Theory 2024 | July 2024
-
Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs
Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Matthew B. Blaschko, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang
June 2024
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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
NeurIPS 2024 | June 2024
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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
CVPR 2024 | June 2024
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Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
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Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation
Xuefei Ning, Zinan Lin, Zixuan Zhou, Zifu Wang, Huazhong Yang, Yu Wang
ICLR 2024 | May 2024
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Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
-
Mixture-of-Linear-Experts for Long-term Time Series Forecasting
Ronghao Ni, Zinan Lin, Shuaiqi Wang, Giulia Fanti
AISTATS 2024 | May 2024
-
Improving the Training of Rectified Flows
Sangyun Lee, Zinan Lin, Giulia Fanti
NeurIPS 2024 | May 2024
-
Rescaling Intermediate Features Makes Trained Consistency Models Perform Better
Junyi Zhu, Zinan Lin, Enshu Liu, Xuefei Ning, Matthew B. Blaschko
ICLR (TinyPapers) 2024 | May 2024
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Summary Statistic Privacy in Data Sharing
Zinan Lin, Shuaiqi Wang, Vyas Sekar, Giulia Fanti
IEEE Journal on Selected Areas in Information Theory | March 2024
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Training Private and Efficient Language Models with Synthetic Data from LLMs
Da Yu, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Janardhan (Jana) Kulkarni, Zinan Lin, Chulin Xie, Huishuai Zhang, Wanrong Zhang
NeurIPS 2023 SoLaR Workshop | December 2023
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OMS-DPM: Optimizing the Model Schedule for Diffusion Probabilistic Models
Enshu Liu, Xuefei Ning, Zinan Lin, Huazhong Yang, Yu Wang
ICML 2023 | July 2023
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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 T. Truong, Simran Arora, Mantas Mazeika, Dan Hendrycks, Zinan Lin, Yu Cheng, Sanmi Koyejo, Dawn Song, Bo Li
NeurIPS 2023 | June 2023
Outstanding Paper Award
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DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis
Chen Gong, Kecen Li, Zinan Lin, Tianhao Wang
CCS 2025 | July 2025
-
Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Models
Zinan Lin, Tadas Baltrusaitis, Sergey Yekhanin
February 2025
-
Inferentially-Private Private Information
Shuaiqi Wang, Shuran Zheng, Zinan Lin, Giulia Fanti, Zhiwei Steven Wu
WWW 2025 | February 2025
-
MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models
Chejian Xu, Jiawei Zhang, Zhaorun Chen, Chulin Xie, Mintong Kang, Zhuowen Yuan, Zidi Xiong, Chenhui Zhang, Lingzhi Yuan, Yi Zeng, Peiyang Xu, Chengquan Guo, Andy Zhou, Jeffrey Ziwei Tan, Zhun Wang, Alexander Xiong, Xuandong Zhao, Yu Gai, Francesco Pinto, Yujin Potter, Zhen Xiang, Zinan Lin, Dan Hendrycks, Dawn Song, Bo Li
ICLR 2025 | February 2025
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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
NeurIPS 2024 | October 2024
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Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin
ICML 2024 | July 2024
Spotlight
-
Statistic Maximal Leakage
Shuaiqi Wang, Zinan Lin, Giulia Fanti
IEEE International Symposium on Information Theory 2024 | July 2024
-
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
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Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
-
Efficiently Computing Similarities to Private Datasets
Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski
ICLR 2024 | May 2024
-
Selective Pre-training for Private Fine-tuning
Da Yu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang
TMLR | May 2024
-
Summary Statistic Privacy in Data Sharing
Zinan Lin, Shuaiqi Wang, Vyas Sekar, Giulia Fanti
IEEE Journal on Selected Areas in Information Theory | March 2024
-
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 T. Truong, Simran Arora, Mantas Mazeika, Dan Hendrycks, Zinan Lin, Yu Cheng, Sanmi Koyejo, Dawn Song, Bo Li
NeurIPS 2023 | June 2023
Outstanding Paper Award
-
-
-
ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation
Tianchen Zhao, Tongcheng Fang, Enshu Liu, Wan Rui, Widyadewi Soedarmadji, Shiyao Li, Zinan Lin, Guohao Dai, Shengen Yan, Huazhong Yang, Xuefei Ning
ICLR 2025 | February 2025
-
MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models
Chejian Xu, Jiawei Zhang, Zhaorun Chen, Chulin Xie, Mintong Kang, Zhuowen Yuan, Zidi Xiong, Chenhui Zhang, Lingzhi Yuan, Yi Zeng, Peiyang Xu, Chengquan Guo, Andy Zhou, Jeffrey Ziwei Tan, Zhun Wang, Alexander Xiong, Xuandong Zhao, Yu Gai, Francesco Pinto, Yujin Potter, Zhen Xiang, Zinan Lin, Dan Hendrycks, Dawn Song, Bo Li
ICLR 2025 | February 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 | February 2025
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Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching
Enshu Liu, Xuefei Ning, Yu Wang, Zinan Lin
ICLR 2025 | February 2025
-
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
ECCV 2024 | July 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
CVPR 2024 | June 2024
-
Improving the Training of Rectified Flows
Sangyun Lee, Zinan Lin, Giulia Fanti
NeurIPS 2024 | May 2024
-
Rescaling Intermediate Features Makes Trained Consistency Models Perform Better
Junyi Zhu, Zinan Lin, Enshu Liu, Xuefei Ning, Matthew B. Blaschko
ICLR (TinyPapers) 2024 | May 2024
-
OMS-DPM: Optimizing the Model Schedule for Diffusion Probabilistic Models
Enshu Liu, Xuefei Ning, Zinan Lin, Huazhong Yang, Yu Wang
ICML 2023 | July 2023
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Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin
ICML 2024 | July 2024
Spotlight
-
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
-
Efficiently Computing Similarities to Private Datasets
Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski
ICLR 2024 | May 2024
-
Selective Pre-training for Private Fine-tuning
Da Yu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang
TMLR | May 2024
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Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin
ICML 2024 | July 2024
Spotlight
-
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
-
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Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation
Xuefei Ning, Zinan Lin, Zixuan Zhou, Zifu Wang, Huazhong Yang, Yu Wang
ICLR 2024 | May 2024
-
-
-
DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis
Chen Gong, Kecen Li, Zinan Lin, Tianhao Wang
CCS 2025 | July 2025
-
Scaling Textual Gradients via Sampling-Based Momentum
Zixin Ding, Junyuan Hong, Jiachen T. Wang, Zinan Lin, Zhangyang Wang, Yuxin Chen
ICML 2025 Workshop on Test-Time Adaptation | June 2025
-
Inferentially-Private Private Information
Shuaiqi Wang, Shuran Zheng, Zinan Lin, Giulia Fanti, Zhiwei Steven Wu
WWW 2025 | February 2025
-
ViDiT-Q: Efficient and Accurate Quantization of Diffusion Transformers for Image and Video Generation
Tianchen Zhao, Tongcheng Fang, Enshu Liu, Wan Rui, Widyadewi Soedarmadji, Shiyao Li, Zinan Lin, Guohao Dai, Shengen Yan, Huazhong Yang, Xuefei Ning
ICLR 2025 | February 2025
-
MMDT: Decoding the Trustworthiness and Safety of Multimodal Foundation Models
Chejian Xu, Jiawei Zhang, Zhaorun Chen, Chulin Xie, Mintong Kang, Zhuowen Yuan, Zidi Xiong, Chenhui Zhang, Lingzhi Yuan, Yi Zeng, Peiyang Xu, Chengquan Guo, Andy Zhou, Jeffrey Ziwei Tan, Zhun Wang, Alexander Xiong, Xuandong Zhao, Yu Gai, Francesco Pinto, Yujin Potter, Zhen Xiang, Zinan Lin, Dan Hendrycks, Dawn Song, Bo Li
ICLR 2025 | February 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 | February 2025
-
Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching
Enshu Liu, Xuefei Ning, Yu Wang, Zinan Lin
ICLR 2025 | February 2025
-
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
NeurIPS 2024 | October 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
ECCV 2024 | July 2024
-
Differentially Private Synthetic Data via Foundation Model APIs 2: Text
Chulin Xie, Zinan Lin, Arturs Backurs, Sivakanth Gopi, Da Yu, Huseyin Inan, Harsha Nori, Haotian Jiang, Huishuai Zhang, Yin Tat Lee, Bo Li, Sergey Yekhanin
ICML 2024 | July 2024
Spotlight
-
Statistic Maximal Leakage
Shuaiqi Wang, Zinan Lin, Giulia Fanti
IEEE International Symposium on Information Theory 2024 | July 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
NeurIPS 2024 | June 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
CVPR 2024 | June 2024
-
Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation
Xinyu Tang, Richard Shin, Huseyin Inan, Andre Manoel, Fatemehsadat Mireshghallah, Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Robert Sim
ICLR 2024 | May 2024
-
Skeleton-of-Thought: Prompting LLMs for Efficient Parallel Generation
Xuefei Ning, Zinan Lin, Zixuan Zhou, Zifu Wang, Huazhong Yang, Yu Wang
ICLR 2024 | May 2024
-
Differentially Private Synthetic Data via Foundation Model APIs 1: Images
Zinan Lin, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Harsha Nori, Sergey Yekhanin
ICLR 2024 | May 2024
-
Mixture-of-Linear-Experts for Long-term Time Series Forecasting
Ronghao Ni, Zinan Lin, Shuaiqi Wang, Giulia Fanti
AISTATS 2024 | May 2024
-
Improving the Training of Rectified Flows
Sangyun Lee, Zinan Lin, Giulia Fanti
NeurIPS 2024 | May 2024
-
Efficiently Computing Similarities to Private Datasets
Arturs Backurs, Zinan Lin, Sepideh Mahabadi, Sandeep Silwal, Jakub Tarnawski
ICLR 2024 | May 2024
-
Rescaling Intermediate Features Makes Trained Consistency Models Perform Better
Junyi Zhu, Zinan Lin, Enshu Liu, Xuefei Ning, Matthew B. Blaschko
ICLR (TinyPapers) 2024 | May 2024
-
Training Private and Efficient Language Models with Synthetic Data from LLMs
Da Yu, Arturs Backurs, Sivakanth Gopi, Huseyin Inan, Janardhan (Jana) Kulkarni, Zinan Lin, Chulin Xie, Huishuai Zhang, Wanrong Zhang
NeurIPS 2023 SoLaR Workshop | December 2023
-
OMS-DPM: Optimizing the Model Schedule for Diffusion Probabilistic Models
Enshu Liu, Xuefei Ning, Zinan Lin, Huazhong Yang, Yu Wang
ICML 2023 | July 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 T. Truong, Simran Arora, Mantas Mazeika, Dan Hendrycks, Zinan Lin, Yu Cheng, Sanmi Koyejo, Dawn Song, Bo Li
NeurIPS 2023 | June 2023
Outstanding Paper Award
-
-
-
-
Efficient Expert Pruning for Sparse Mixture-of-Experts Language Models: Enhancing Performance and Reducing Inference Costs
Enshu Liu, Junyi Zhu, Zinan Lin, Xuefei Ning, Matthew B. Blaschko, Shengen Yan, Guohao Dai, Huazhong Yang, Yu Wang
June 2024
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Selective Pre-training for Private Fine-tuning
Da Yu, Sivakanth Gopi, Janardhan (Jana) Kulkarni, Zinan Lin, Saurabh Naik, Tomasz Lukasz Religa, Jian Yin, Huishuai Zhang
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