Yaqing Guo — accepted AI-conference papers

2026

Just Y-Prediction: Enabling Historical Cumulative Inconsistency in Label Diffusion for Learning with Noisy Label

Senyu Hou, Gaoxia Jiang, Xinyi Zheng, Yaqing Guo, Shuna Liang, Wenjian Wang

ICML 2026poster

Label noise is pervasive in real-world datasets and significantly compromises model generalization, fueling extensive research into Learning with Noisy Labels (LNL). Most LNL methods focus on robust discriminative learning, while recent generative classifiers such as label diffusion models (LDMs) sh…

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2025

Directional Label Diffusion Model for Learning from Noisy Labels

Senyu Hou, Gaoxia Jiang, Jia Zhang, Shangrong Yang, Husheng Guo, Yaqing Guo +1

CVPR 2025poster

In image classification, the label quality of training data critically influences model generalization, especially for deep neural networks (DNNs). Traditionally, learning from noisy labels (LNL) can improve the generalization of DNNs through complex architectures or a series of robust techniques, b…

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