AI RESEARCH
A Modular LLM Framework for Explainable Price Outlier Detection
arXiv CS.CL
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ArXi:2603.20636v1 Announce Type: new Detecting product price outliers is important for retail and e-commerce s as erroneous or unexpectedly high prices adversely affect competitiveness, revenue, and consumer trust. Classical techniques offer simple thresholds while ignoring the rich semantic relationships among product attributes. We propose an agentic Large Language Model (LLM) framework that treats outlier price flagging as a reasoning task grounded in related product detection and comparison.