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LLMs can learn to synthesize data more effectively by accumulating and transferring experience across a stream of sequential synthesis tasks, opening the door to more efficient and adaptable synthetic data generation.
Freezing a Sparse Autoencoder's encoder creates a reusable "safety dictionary" that generalizes to new risks in text-to-image diffusion models, offering a more robust alternative to fixed-layer steering.
