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Traitement quantique des langues : 'etat de l'art

arXiv 2406.15370 ↗First posted 9 Apr 2024cs.CLcited by 0

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Abstract (arXiv)

This article presents a review of quantum computing research works for Natural Language Processing (NLP). Their goal is to improve the performance of current models, and to provide a better representation of several linguistic phenomena, such as ambiguity and long range dependencies. Several families of approaches are presented, including symbolic diagrammatic approaches, and hybrid neural networks. These works show that experimental studies are already feasible, and open research perspectives on the conception of new models and their evaluation.

Key facts. No citing papers in the map yet (data through 14 Oct 2026). Builds on 24 of its 62 references that are in the map. First posted on arXiv 9 Apr 2024.

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References · 24

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12 more
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