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cs.CV2025
Improving VQA Reliability: A Dual-Assessment Approach with Self-Reflection and Cross-Model Verification
Xixian Wu, Yang Ou, Pengchao Tian +4
Vision-language models (VLMs) have demonstrated significant potential in Visual Question Answering (VQA). However, the susceptibility of VLMs to hallucinations can lead to overconf…
cs.CV2025
OMUDA: Omni-level Masking for Unsupervised Domain Adaptation in Semantic Segmentation
Yang Ou, Xiongwei Zhao, Xinye Yang +5
Unsupervised domain adaptation (UDA) enables semantic segmentation models to generalize from a labeled source domain to an unlabeled target domain. However, existing UDA methods st…