A self-supervision method makes multimodal LLMs align their input image embeddings with the model's own refined internal representations, improving visual QA scores over LLaVA baselines.
Towards monose- manticity: Decomposing language models with dictionary learning
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BASIC: Boosting Visual Alignment with Intrinsic Refined Embeddings in Multimodal Large Language Models
A self-supervision method makes multimodal LLMs align their input image embeddings with the model's own refined internal representations, improving visual QA scores over LLaVA baselines.