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cs.CV2025
Learning What Matters: Prioritized Concept Learning via Relative Error-driven Sample Selection
Shivam Chandhok, Qian Yang, Oscar Manas +3
Instruction tuning has been central to the success of recent vision-language models (VLMs), but it remains expensive-requiring large-scale datasets, high-quality annotations, and l…
cs.CV2024
Benchmarking Vision Language Models for Cultural Understanding
Shravan Nayak, Kanishk Jain, Rabiul Awal +5
Foundation models and vision-language pre-training have notably advanced Vision Language Models (VLMs), enabling multimodal processing of visual and linguistic data. However, their…