（* indicates equal contributions，† indicates corresponding author）
2025
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Yujun Huang, Bin Chen, Naiqi Li, Baoyi An, Shu-Tao Xia, Yaowei Wang. MB-RACS: Measurement-Bounds-based Rate-Adaptive Image Compressed Sensing Network. IEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2025.
[paper]
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Xinyi Zhang, Naiqi Li, Angela Dai. DNF: Unconditional 4D Generation with Dictionary-based Neural Fields. Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
[paper]
[project]
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Yujun Liu, Yaohua Zha, Naiqi Li, Tao Dai, Bin Chen and Shu-Tao Xia. Expert-Enhanced Masked Point Modeling for Point Cloud Self-supervised Learning. International Conference on Robotics and Automation (ICRA), 2025.
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Yujun Liu, Chenhui Song, Peiyuan Liu, Naiqi Li, Tao Dai, Jigang Bao, Yong Jiang and Shu-Tao Xia. MERA: Mixture of Experts with Retrieval-Augmented Representation for Modeling Diversified Stock Patterns. International World Wide Web Conference (WWW), Short Paper, 2025.
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Peiyuan Liu, Hang Guo, Tao Dai, Naiqi Li†, Jigang Bao, Xudong Ren, Yong Jiang, Shu-Tao Xia. CALF: Aligning LLMs for Time Series Forecasting via Cross-modal Fine-Tuning. AAAI Conference on Artificial Intelligence (AAAI), 2025.
[paper]
[github]
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Jiarui Yang, Tao Dai, Yufei Zhu, Naiqi Li, Jinmin Li, Shu-Tao Xia. Diffusion Prior Interpolation for Flexibility Real-World Face Super-Resolution. AAAI Conference on Artificial Intelligence (AAAI), 2025.
2024
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Naiqi Li, Zhikang Xia, Yiming Li, Ercan E. Kuruoglu, Yong Jiang, Shu-Tao Xia. Portfolio Selection via Graph-Aware Gaussian Processes with Generalized Gaussian Likelihood. IEEE Transactions on Artificial Intelligence (TAI), 2024.
[paper]
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Naiqi Li*†, Wenjie Li*, Yinghua Gao, Yiming Li, Jigang Bao, Ercan E. Kuruoglu, Yong Jiang, Shu-Tao Xia. Node-Level Graph Regression with Deep Gaussian Process Models. IEEE Transactions on Artificial Intelligence (TAI), 2024.
[paper]
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Yaohua Zha, Naiqi Li, Yanzi Wang, Tao Dai, Hang Guo, Bin Chen, Zhi Wang, Zhihao Ouyang, Shu-Tao Xia. LCM: Locally Constrained Compact Point Cloud Model for Masked Point Modeling. Conference on Neural Information Processing Systems (NeurIPS), 2024.
[paper]
[poster]
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Tao Dai, Beiliang Wu, Peiyuan Liu, Naiqi Li†, Xue Yuerong, Shu-Tao Xia, Zexuan Zhu. DDN: Dual-domain Dynamic Normalization for Non-stationary Time Series Forecasting. Conference on Neural Information Processing Systems (NeurIPS), 2024.
[paper]
[github]
[poster]
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Shiqi Dai, Xuanyu Zhu, Naiqi Li, Tao Dai, Zhi Wang. Procedural Level Generation with Diffusion Models from a Single Example. AAAI Conference on Artificial Intelligence (AAAI), 2024.
[paper]
[github]
[poster]
[slides]
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Bolin Jiang, Yuqiu Xie, Jiawei Li, Naiqi Li†, Yong Jiang, Shu-Tao Xia. CAGEN: Controllable Anomaly Generator using Diffusion Model. International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024.
[paper]
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Peiyuan Liu, Beiliang Wu, Naiqi Li†, Tao Dai†, Fengmao Lei, Jigang Bao, Yong Jiang, Shu-Tao Xia. WFTNet: Exploiting Global and Local Periodicity in Long-Term Time Series Forecasting. International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2024.
[paper]
[github]
[poster]
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Tao Dai, Beiliang Wu, Peiyuan Liu, Naiqi Li†, Jigang Bao, Yong Jiang, Shu-Tao Xia. Periodicity Decoupling Framework for Long-term Series Forecasting. International Conference on Learning Representations (ICLR), 2024.
[paper]
[github]
[poster]
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Yuqiu Xie, Bolin Jiang, Jiawei Li, Naiqi Li†, Bin Chen†, Tao Dai, Yuang Peng, Shu-Tao Xia. GladCoder: Stylized QR Code Generation with Grayscale-Aware Denoising Process. International Joint Conference on Artificial Intelligence (IJCAI), 2024.
[paper]
[poster]
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Bolin Jiang, Yuqiu Xie, Jiawei Li, Naiqi Li†, Bin Chen†, Shu-Tao Xia. IGSPAD: Inverting 3D Gaussian Splatting for Pose-agnostic Anomaly Detection. ACM International Conference on Multimedia (MM), 2024.
[paper]
2023
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Guanghao Meng, Tao Dai, Bin Chen, Naiqi Li, Yong Jiang, Shu-Tao Xia. Difficulty-Aware Data Augmentor for Scene Text Recognition. International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2023.
[paper]
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Xinyi Zhang*, Naiqi Li*†, Jiawei Li, Tao Dai, Yong Jiang, Shu-Tao Xia. Unsupervised Surface Anomaly Detection with Diffusion Probabilistic Model. International Conference on Computer Vision (ICCV), 2023.
[paper]
[github]
[poster]
2022
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Naiqi Li*, Wenjie Li*, Yong Jiang, Shu-Tao Xia. Deep Dirichlet process mixture models. Conference on Uncertainty in Artificial Intelligence (UAI), 2022.
[paper]
[poster]
2021
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Xiang Liu, Naiqi Li, Shu-Tao Xia. GDTW: A Novel Differentiable DTW Loss for Time Series Tasks. International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021.
[paper]
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Naiqi Li, Yinghua Gao, Wenjie Li, Yong Jiang, Shu-Tao Xia. H-GPR: A Hybrid Strategy for Large-Scale Gaussian Process Regression. International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2021.
[paper]
2020
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Yinghua Gao*, Naiqi Li*, Ning Ding, Yiming Li, Tao Dai, Shu-Tao Xia. Generalized Local Aggregation for Large Scale Gaussian Process Regression. International Joint Conference on Neural Networks (IJCNN), 2020.
[paper]
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Naiqi Li*, Wenjie Li*, Jifeng Sun, Yinghua Gao, Yong Jiang, Shu-Tao Xia. Stochastic Deep Gaussian Processes over Graphs. Conference on Neural Information Processing Systems (NeurIPS), 2020.
[paper]
[poster]
~2019
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Peiming Mo, Naiqi Li, Yongmei Liu. Automatic Verification of Golog Programs via Predicate Abstraction. European Conference on Artificial Intelligence (ECAI), 2016.
[paper]
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Naiqi Li, Yongmei Liu. Automatic Verification of Partial Correctness of Golog Programs. International Joint Conference on Artificial Intelligence (IJCAI), 2015.
[paper]
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Naiqi Li, Yi Fan, Yongmei Liu. Reasoning about State Constraints in the Situation Calculus. International Joint Conference on Artificial Intelligence (IJCAI), 2013.
[paper]
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Yi Fan, Minghui Cai, Naiqi Li, Yongmei Liu. A First-Order Interpreter for Knowledge-Based Golog with Sensing based on Exact Progression and Limited Reasoning. AAAI Conference on Artificial Intelligence (AAAI), 2012.
[paper]
![[poster]](documents\poster\diffusioncraft.png){kind=link}
![[poster]](documents\poster\ICLR24.png){kind=link}