| 2026 | CHI | Beyond Input-Output: Rethinking Creativity through Design-by-Analogy in Human-AI Collaboration. | Xuechen Li, Shuai Zhang, Nan Cao, Qing Chen |
| 2025 | CHI | ViviClay: Fabricating Ceramics with Animated Surface Effects. | Jingxin Ye, Qiaoqiao Jin, Chao Yuan, Xuechen Li, Yang Shi, Qing Chen, Nan Cao, Guanhong Liu |
| 2025 | HCI | All Goes Well: A Self-healing Service Design Study by Creating Bracelets for Young Chinese People. | Peiyuan Ge, Jiahe Wu, Yihan Zhang, Jie Yang, Yue Zhu, Xuechen Li, Haipeng Duan, Wenhao Jiang, Yunsheng Su |
| 2025 | UIST | ViviClay: Designing and Fabricating Ceramics with Animation Effects on Physical Surfaces. | Guanhong Liu, Jingxin Ye, Qiaoqiao Jin, Chao Yuan, Xuechen Li, Yang Shi, Qing Chen, Nan Cao |
| 2024 | ICML | Linguistic Calibration of Long-Form Generations. | Neil Band, Xuechen Li, Tengyu Ma, Tatsunori Hashimoto |
| 2024 | SP | Exploiting Programmatic Behavior of LLMs: Dual-Use Through Standard Security Attacks. | Daniel Kang, Xuechen Li, Ion Stoica, Carlos Guestrin, Matei Zaharia, Tatsunori Hashimoto |
| 2023 | ACL | Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe. | Xiang Yue, Huseyin A. Inan, Xuechen Li, Girish Kumar, Julia McAnallen, Hoda Shajari, Huan Sun, David Levitan, Robert Sim |
| 2023 | CBMS | Multi-scale Contrastive Learning for Gastroenteroscopy Classification. | Dan Li, Xuechen Li, Zhibin Peng, Wenting Chen, Linlin Shen, Guangyao Wu |
| 2023 | ICLR | Exploring the Limits of Differentially Private Deep Learning with Group-wise Clipping. | Jiyan He, Xuechen Li, Da Yu, Huishuai Zhang, Janardhan Kulkarni, Yin Tat Lee, Arturs Backurs, Nenghai Yu, Jiang Bian |
| 2023 | MICCAI | TCEIP: Text Condition Embedded Regression Network for Dental Implant Position Prediction. | Xinquan Yang, Jinheng Xie, Xuguang Li, Xuechen Li, Xin Li, Linlin Shen, Yongqiang Deng |
| 2022 | AISTATS | Infinitely Deep Bayesian Neural Networks with Stochastic Differential Equations. | Winnie Xu, Ricky T. Q. Chen, Xuechen Li, David Duvenaud |
| 2022 | CBMS | Contrastive learning-based Adenoid Hypertrophy Grading Network Using Nasoendoscopic Image. | Siting Zheng, Xuechen Li, Mingmin Bi, Yuxuan Wang, Haiyan Liu, Xiaoshan Feng, Yunping Fan, Linlin Shen |
| 2022 | ICLR | Large Language Models Can Be Strong Differentially Private Learners. | Xuechen Li, Florian Tramr, Percy Liang, Tatsunori Hashimoto |
| 2022 | MICCAI | Sample Hardness Based Gradient Loss for Long-Tailed Cervical Cell Detection. | Minmin Liu, Xuechen Li, Xiangbo Gao, Junliang Chen, Linlin Shen, Huisi Wu |
| 2021 | CBMS | Classification and Localization Consistency Regularized Student-Teacher Network for Semi-supervised Cervical Cell Detection. | Menglu Zhang, Xuechen Li, Linlin Shen |
| 2021 | ICLR | When does preconditioning help or hurt generalization? | Shun-ichi Amari, Jimmy Ba, Roger Baker Grosse, Xuechen Li, Atsushi Nitanda, Taiji Suzuki, Denny Wu, Ji Xu |
| 2021 | ICML | Neural SDEs as Infinite-Dimensional GANs. | Patrick Kidger, James Foster, Xuechen Li, Terry J. Lyons |
| 2020 | AISTATS | Scalable Gradients for Stochastic Differential Equations. | Xuechen Li, Ting-Kam Leonard Wong, Ricky T. Q. Chen, David Duvenaud |
| 2020 | CBMS | Automatic Primary Gross Tumor Volume Segmentation for Nasopharyngeal Carcinoma using ResSE-UNet. | Zhihao Jin, Xuechen Li, Linlin Shen, Jinyi Lang, Jie Li, Junxiang Wu, Peng Xu, Jiang Duan |
| 2018 | ICLR | Isolating Sources of Disentanglement in Variational Autoencoders. | Tian Qi Chen, Xuechen Li, Roger B. Grosse, David Duvenaud |
| 2018 | ICML | Inference Suboptimality in Variational Autoencoders. | Chris Cremer, Xuechen Li, David Duvenaud |
| 2018 | ICTAI | GT-Net: A Deep Learning Network for Gastric Tumor Diagnosis. | Yuexiang Li, Xinpeng Xie, Shaoxiong Liu, Xuechen Li, Linlin Shen |
| 2015 | MMM | An Automatic Rib Segmentation Method on X-Ray Radiographs. | Xuechen Li, Suhuai Luo, Qingmao Hu |
| 2009 | ISNN | Synchronization and Lag Synchronization of Chaotic Networks. | Zunshui Cheng, Youming Xin, Xuechen Li, Jianmin Xing |