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Hallucinations in diffusion models can be reduced by up to 25% without sacrificing image quality, thanks to a novel score modulation technique.
Diffusion language models inherently signal factual uncertainty during generation, outperforming even trained hallucination detectors, and OSCAR leverages this to reduce hallucinations.
