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Mitigating Hallucination in Large Vision-Language Models via Adaptive Attention Calibration
Large vision-language models (LVLMs) achieve impressive performance on multimodal tasks but often suffer from hallucination, and confidently describe objects or attributes not present in the image. Current training-free interventions struggle to maintain accuracy in open-ended and long-form generati
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