Concept shift vectors, computed as mean activation differences, can partially recover fine-tuned multimodal LLM concepts and steer model outputs without additional training.
What makes multimodal in-context learning work? In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR) Workshops, pages 1539–1550, 2024
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Analyzing Finetuning Representation Shift for Multimodal LLMs Steering
Concept shift vectors, computed as mean activation differences, can partially recover fine-tuned multimodal LLM concepts and steer model outputs without additional training.