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MUSE

modelactivemuse-fedab13e·2 events·first seen 28d ago

Aliases: MUSE

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6arXiv · cs.CL·21d ago·source ↗

MUSE Framework Disentangles Sycophancy from Epistemic Uncertainty in LLM Conformity

This paper introduces MUSE, a two-stage evaluation framework that separates two distinct mechanisms driving LLM conformity to user pushback: sycophantic conformity (yielding despite high certainty) and uncertainty-driven conformity (yielding proportional to epistemic uncertainty). The authors demonstrate that prior work's attribution of all conformity to RLHF-induced sycophancy is incomplete, as a model's inference-time uncertainty is an independent contributing factor. Ablation studies show both conformity types increase with perceived user expertise and plausibility of user suggestions, pointing toward distinct intervention strategies for each mechanism.

4Hugging Face Blog·28d ago·source ↗

Welcome aMUSEd: Efficient Text-to-Image Generation

Hugging Face introduces aMUSEd, a text-to-image model based on the MUSE architecture that prioritizes efficiency over raw quality. The model is designed to be smaller and faster than diffusion-based alternatives, making it more accessible for deployment. It is released with integration into the Diffusers library.