First non-vacuous PAC-Bayes certificates for large vision and language models in the 100-example low-shot regime, obtained by reinterpreting model merging as a low-dimensional posterior.
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Model Merging is Secretly Certifiable: Non-Vacuous Generalisation Bounds for Low-Shot Learning
First non-vacuous PAC-Bayes certificates for large vision and language models in the 100-example low-shot regime, obtained by reinterpreting model merging as a low-dimensional posterior.