MIMIC is a new inversion framework that recovers visual concepts from VLM internal states using joint inversion, feature alignment, and three regularizers.
Deep residual learning for image recognition
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UNVERDICTED 2representative citing papers
GHL combines local Oja's rule with competitive learning and a global sign signal to outperform prior Hebbian methods and narrow the performance gap with backpropagation on large-scale tasks.
citing papers explorer
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MIMIC: Multimodal Inversion for Model Interpretation and Conceptualization
MIMIC is a new inversion framework that recovers visual concepts from VLM internal states using joint inversion, feature alignment, and three regularizers.
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Hebbian Learning with Global Direction
GHL combines local Oja's rule with competitive learning and a global sign signal to outperform prior Hebbian methods and narrow the performance gap with backpropagation on large-scale tasks.