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A unified framework reveals that the choice of tokenization and vocabulary topology can significantly influence the performance of discrete diffusion models, unlocking new avenues for optimization.
Harnessing the internal states of LLMs, SIREN outperforms traditional guard models while using a fraction of the parameters, revolutionizing harmful content detection.
