Looking Back and Forth: Cross-Image Attention Calibration and Attentive Preference Learning for Multi-Image Hallucination Mitigation
Looking Back and Forth: Cross-Image Attention Calibration and Attentive Preference Learning for Multi-Image Hallucination Mitigation explores Mitigate hallucinations in multi-image tasks with a cross-image attention calibration and preference learning framework, enhancing inter-image interactions and grounding predictions in visual evidence.. Commercial viability score: 7/10 in Multi-Image Processing.
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