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cs.CV2026★ 1 cited
Are Multimodal Large Language Models Good Annotators for Image Tagging?
Ming-Kun Xie, Jia-Hao Xiao, Zhiqiang Kou +3
Image tagging, a fundamental vision task, traditionally relies on human-annotated datasets to train multi-label classifiers, which incurs significant labor and costs. While Multimo…
cs.CV2025
What Makes "Good" Distractors for Object Hallucination Evaluation in Large Vision-Language Models?
Ming-Kun Xie, Jia-Hao Xiao, Gang Niu +4
Large Vision-Language Models (LVLMs), empowered by the success of Large Language Models (LLMs), have achieved impressive performance across domains. Despite the great advances in L…
cs.CV2024
Counterfactual Reasoning for Multi-Label Image Classification via Patching-Based Training
Ming-Kun Xie, Jia-Hao Xiao, Pei Peng +3
The key to multi-label image classification (MLC) is to improve model performance by leveraging label correlations. Unfortunately, it has been shown that overemphasizing co-occurre…