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Found 3 papers, 2 papers with code
Automatic Discovery of Visual Circuits
To date, most discoveries of network subcomponents that implement human-interpretable computations in deep vision models have involved close study of single units and large amounts of human labor.
FIND: A Function Description Benchmark for Evaluating Interpretability Methods
FIND contains functions that resemble components of trained neural networks, and accompanying descriptions of the kind we seek to generate.
Multimodal Neurons in Pretrained Text-Only Transformers
Language models demonstrate remarkable capacity to generalize representations learned in one modality to downstream tasks in other modalities.
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