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Hanyang University
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DPO-tuned LLMs systematically achieve less than a third of requested emotional intensity because preference optimization cannot reward behavioral extremes that base models never sample.
Vetoing unstable tokens can boost dMLLM reasoning accuracy by up to 9% without any extra training costs.
