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papersSEP 10 04:00 UTC

Study examines hybrid quantum-classical NLP classification using compressed semantic embeddings

A new arXiv paper tackles the mismatch between high-dimensional text embeddings and the limited input capacity of near-term quantum circuits. The authors experiment with compressing semantic representations so they can feed into hybrid quantum-classical classifiers for NLP tasks. The work offers an empirical look at how much representation reduction is viable for quantum machine learning applications.

arXivhybrid quantum-classical computingmodel-compressionnatural-language-processingquantum-machine-learningsemantic embeddings

COVERAGE · 1 REPORT · LINKS GO TO THE ORIGINAL OUTLETS

arXiv cs.LGHybrid Quantum-Classical NLP Classification with Compact Semantic Representations: An Experimental Analysis of Representation Compression ↗SEP 10 04:00 UTC

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