UC Berkeley and NYU AI Research Explores the Gap Between the Visual Embedding Space of Clip and Vision-only Self-Supervised Learning

MLLMs, or multimodal large language models, have been advancing lately. By incorporating images into large language models (LLMs) and harnessing the capabilities of LLMs, MLLMs demonstrate exceptional skill in tasks including visual question answering, instruction following, and image understanding. Studies have seen a significant flaw in these models despite their improvements; they still have some […]

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