Entanglement as Memory: Mechanistic Interpretability of Quantum Language Models

ArXi:2603.26494v1 Announce Type: cross Quantum language models have shown competitive performance on sequential tasks, yet whether trained quantum circuits exploit genuinely quantum resources -- or merely embed classical computation in quantum hardware -- remains unknown. Prior work has evaluated these models through endpoint metrics alone, without examining the memory strategies they actually learn internally. We