Identity Loss and Seamless Recovery in LLMs at High Temperatures
cephaloform · x · 2026-07-30
A developer observed that under high-temperature generation, models (like Mistral and Llama) sometimes briefly lose their identity at the beginning of a message but then seamlessly recover and integrate the preset identity (like Claude) later. This might be due to RL training masking user replies from the loss function, causing the model to rely on base user modeling from mid-training, with the RL delta pulling it slightly out of distribution (OOD).
Related event: Developers Attribute Claude's Odd Outputs to User Modeling, Not Thought(3 posts)→
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