attention distraction 1cross-head attention 1dynamic attention 1hallucination mitigation 1multimodal language models 1visual grounding 1
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cs.CV2026
Correcting Visual Blur Induced by Attention Distraction to Reduce Hallucinations: Algorithm and Theory
Quanjiang Li, Zhiming Liu, Wei Luo +2
The paper investigates why multimodal large language models hallucinate objects, linking it to an attention distraction effect similar to human visual blur, and introduces AFIP, a…
cs.CV2026
ProtoDCS: Towards Robust and Efficient Open-Set Test-Time Adaptation for Vision-Language Models
Wei Luo, Yangfan Ou, Jin Deng +4
Large-scale Vision-Language Models (VLMs) exhibit strong zero-shot recognition, yet their real-world deployment is challenged by distribution shifts. While Test-Time Adaptation (TT…
cs.CV2025
Test-Time Model Adaptation for Quantized Neural Networks
Zeshuai Deng, Guohao Chen, Shuaicheng Niu +6
Quantizing deep models prior to deployment is a widely adopted technique to speed up inference for various real-time applications, such as autonomous driving. However, quantized mo…