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Target-aware data selection and VLM-based caption refinement can boost food image retrieval performance by over 19%, revealing the potential of fine-tuning multimodal models with curated data.
Injecting LLM-derived ingredient labels into food image segmentation boosts accuracy to state-of-the-art levels while keeping resource demands low.
