AINeutralarXiv – CS AI · 15h ago6/10
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It's Not Always Sycophancy: Measuring LLM Conformity as a Function of Epistemic Uncertainty
Researchers introduce MUSE, a framework that disentangles two distinct mechanisms driving LLM conformity: sycophancy learned through reinforcement learning and uncertainty-driven conformity based on epistemic uncertainty at inference time. The findings suggest that LLMs don't simply yield to user pushback due to training, but also because they genuinely lack confidence in their initial responses, with both factors amplified when users appear knowledgeable or suggestions seem plausible.