arXiv cs.AIPaperClaude Watch
You Can't Prefer Emotions You Don't Sample: Intensity Undershoot in DPO-Tuned LLMs
This quantifies a real behavioral gap: ask Claude or Llama to respond very excitedly and you get mildly excited. The root cause is training data bias, not architectural. For teams building tone-adaptive or persona-driven assistants, this suggests your tuning pipeline needs synthetic high-intensity examples. It also flags a limitation in preference learning that affects any high-dimensional behavioral control.