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Standard Gaussian initialization can lead to mode collapse, but a new approach using guidance potential posteriors dramatically enhances image diversity.
VLMs can regain lost temporal reasoning abilities without retraining, simply by strategically merging the right layers from their text-only LLM backbone.
