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20222026
most citedInstance-Dependent Label-Noise Learning with Manifold-Regularized Transition Matrix Estimation

5 citations · 17 across the 19 of their papers we have counts for

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cs.CV2026

PAPT++: Risk-Aware Adversarial Tuning and Generation for Single Domain Generalization

Zhipeng Xu, De Cheng, Xinyang Jiang +5

Single domain generalization (SDG) aims to learn a model from one labeled source domain that generalizes to unseen target domains. A common strategy is to enrich the source distrib…

cs.CV2026

Symbiosis-Inspired Knowledge Distillation for Incremental Object Detection

Mingyue Zeng, De Cheng, Zhipeng Xu +3

Incremental object detection (IOD) aims to extend detectors to new categories while retaining previously acquired knowledge. Existing methods often adopt a class incremental learni…

cs.CV2026

Dual-Branch Cross-Projection Debiasing through Diffusion-based Disentanglement

Xiangqian Zhao, Xinyang Jiang, Zhipeng Xu +5

Foundation models trained on biased datasets often rely on spurious correlations between target labels and non-causal attributes, resulting in poor generalization on minority group…

cs.CV2026

Adversarial Domain Prompt Tuning and Generation for Single Domain Generalization

Zhipeng Xu, De Cheng, Xinyang Jiang +3

Single domain generalization (SDG) aims to learn a robust model, which could perform well on many unseen domains while there is only one single domain available for training. One o…

cs.AI2026

Reasoning-Driven Multimodal LLM for Domain Generalization

Zhipeng Xu, Zilong Wang, Xinyang Jiang +3

This paper addresses the domain generalization (DG) problem in deep learning. While most DG methods focus on enforcing visual feature invariance, we leverage the reasoning capabili…