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Critique Before Thinking: Mitigating Hallucination through Rationale-Augmented Instruction Tuning
Despite significant advancements in multimodal reasoning tasks, existing Large Vision-Language Models (LVLMs) are prone to producing visually ungrounded responses when interpreting associated images.
A Pedestrian is Worth One Prompt: Towards Language Guidance Person Re-Identification
Whiteness the impressive capabilities in multimodal understanding of Vision Language Foundation Model CLIP a recent two-stage CLIP-based method employs automated prompt engineering to obtain specific textual labels for classifying pedestrians.
Handling Label Uncertainty for Camera Incremental Person Re-Identification
Specifically, new data collected from new cameras may probably contain an unknown proportion of identities seen before.
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