AI RESEARCH
PRISM: LLM-Guided Semantic Clustering for High-Precision Topics
arXiv CS.LG
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ArXi:2604.03180v1 Announce Type: new In this paper, we propose Precision-Informed Semantic Modeling (PRISM), a structured topic modeling framework combining the benefits of rich representations captured by LLMs with the low cost and interpretability of latent semantic clustering methods. PRISM fine-tunes a sentence encoding model using a sparse set of LLM- provided labels on samples drawn from some corpus of interest. We segment this embedding space with thresholded clustering, yielding clusters that separate closely related topics within some narrow domain.