SSAM: Singular Subspace Alignment for Merging Multimodal Large Language Models
SSAM: Singular Subspace Alignment for Merging Multimodal Large Language Models explores A training-free framework to merge existing multimodal LLMs into a single model capable of handling any combination of input modalities, achieving state-of-the-art performance without new data.. Commercial viability score: 8/10 in LLM Merging.
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