A 160-parameter attention-scaling method, DARA, improves true multimodal in-context learning on a new dataset, TrueMICL, that forces models to use demo images rather than copy text patterns.
Each task is designed with adjustable difficulty levels, such as more diverse con- cepts in novel concept binding, more complex visual patterns in pattern interpretation, etc
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True Multimodal In-Context Learning Needs Attention to the Visual Context
A 160-parameter attention-scaling method, DARA, improves true multimodal in-context learning on a new dataset, TrueMICL, that forces models to use demo images rather than copy text patterns.