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Emotion representation in LLMs varies dramatically across architectures, with some models encoding valence early and others later, revealing a complex landscape of emotional understanding in AI.
Stop hand-tuning reward learning losses: MAVRL learns a shared reward function from diverse feedback signals by treating each as a likelihood within a Bayesian inference framework.
