Linwei Tao

Publications

Peer-reviewed papers, workshop papers, and preprints.

0 papers 0 first-author 0 published 0 preprints
2026
WATS: Wavelet-Aware Temperature Scaling for Reliable Graph Neural Networks
Xiaoyang Li, Linwei Tao, Haohui Lu, Minjing Dong, Junbin Gao, Chang Xu.
CCF-A CORE A* International Conference on Learning Representations (ICLR), 2026.
Task-Adaptive Continual Learning of Vision Language Models via Prototype Routing and Prompt
Lei Pan, Z. Lu, Yuan Zheng, C. Yan, H. Wen, Linwei Tao, Chang Xu.
Neurocomputing, 2026.
Confidence Calibration under Ambiguous Ground Truth
Linwei Tao, Haoyang Luo, Minjing Dong, Chang Xu.
Preprint arXiv:2603.22879, 2026.
Paper Code
2025
Beyond One-Hot Labels: Semantic Mixing for Model Calibration
Haoyang Luo, Linwei Tao, Minjing Dong, Chang Xu.
CCF-A CORE A* International Conference on Machine Learning (ICML), 2025.
Uncertainty Weighted Gradients for Model Calibration
Jinxu Lin, Linwei Tao, Minjing Dong, Chang Xu.
CCF-A CORE A* IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2025.
Diffusion Attribution Score: Evaluating Training Data Influence in Diffusion Model
Jinxu Lin, Linwei Tao, Minjing Dong, Chang Xu.
CCF-A CORE A* Spotlight 5.1% International Conference on Learning Representations (ICLR), 2025.
Paper
Feature Clipping for Uncertainty Calibration
Linwei Tao, Minjing Dong, Chang Xu.
CCF-A CORE A* AAAI Conference on Artificial Intelligence (AAAI), 2025.
Paper Code
KG-UQ: Knowledge Graph-Based Uncertainty Quantification for Long Text in Large Language Models
Yingqing Yuan, Linwei Tao, Haohui Lu, Matloob Khushi, Imran Razzak, Mark Dras, Jian Yang, Usman Naseem.
International World Wide Web Conference (WWW) Workshop, 2025.
Can Large Language Models Express Uncertainty Like Human?
Linwei Tao, Yi-Fan Yeh, Bo Kai, Minjing Dong, Tao Huang, Tom A. Lamb, Jialin Yu, Philip H.S. Torr, Chang Xu.
PreprintarXiv:2509.24202, 2025.
Paper
Revisiting Uncertainty Estimation and Calibration of Large Language Models
Linwei Tao, Yi-Fan Yeh, Minjing Dong, Tao Huang, Philip Torr, Chang Xu.
PreprintarXiv:2505.23854, 2025.
Paper
Sample Margin-Aware Recalibration of Temperature Scaling
Haolan Guo, Linwei Tao, Haoyang Luo, Minjing Dong, Chang Xu.
PreprintarXiv:2506.23492, 2025.
Paper
Mitigating Object Hallucinations in Large Vision-Language Models via Attention Calibration
Younan Zhu, Linwei Tao, Minjing Dong, Chang Xu.
PreprintarXiv:2502.01969, 2025.
Paper
Consistency Calibration: Improving Uncertainty Calibration via Consistency among Perturbed Neighbors
Linwei Tao, Haolan Guo, Minjing Dong, Chang Xu.
PreprintarXiv:2410.12295, 2025.
Paper
2024
A Benchmark Study on Calibration
Linwei Tao, Younan Zhu, Haolan Guo, Minjing Dong, Chang Xu.
CCF-A CORE A* International Conference on Learning Representations (ICLR), 2024.
Paper Dataset Code Project Page Poster Slides
GraphFusion: Integrating Multi-Level Semantic Information with Graph Computing for Enhanced 3D Instance Segmentation
Lei Pan, Wuyang Luan, Yuan Zheng, Junhui Li, Linwei Tao, Chang Xu.
Neurocomputing, 2024.
Paper Code
Visual Imitation Learning with Calibrated Contrastive Representation
Yunke Wang, Linwei Tao, Bo Du, Yutian Lin, Chang Xu.
PreprintarXiv:2401.11396, 2024.
Paper
2023
Dual Focal Loss for Calibration
Linwei Tao, Minjing Dong, Chang Xu.
CCF-A CORE A* International Conference on Machine Learning (ICML), 2023.
Paper Code Poster Slides
Calibrating a Deep Neural Network with Its Predecessors
Linwei Tao, Minjing Dong, Daochang Liu, Changming Sun, Chang Xu.
CCF-B CORE A* International Joint Conference on Artificial Intelligence (IJCAI), 2023.
Paper Code Playground Slides

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