arXiv Machine Learning October 8, 2026 By Bibhas Adhikari, Ramya Srinivasan

A Cognitive-Aware QML-CRL Framework for Detecting Affinity and Romance-Investment Fraud

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The paper introduces a hybrid quantum‑classical framework for detecting affinity and romance‑investment fraud by modeling cognitive biases in manipulative conversations. Dedicated qubits encode key biases, a frame qubit captures temporal order, and a narrative qubit aggregates co‑occurrence via a trainable entanglement layer. The circuit parameters are jointly trained with a classical reinforcement‑learning agent that decides, turn by turn, whether to flag the conversation as an optimal stopping problem, and the model is evaluated on synthetic conversations including hard negatives and legitimate but urgent or pushy sales scenarios.

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