Mu-DisCoCat: A Variational Pipeline for Compositional Generalization on Quantum Processors
Achieving compositional concept generalization (CoCoGen), the ability to understand novel situations by recombining learned primitives, remains a fundamental challenge in artificial intelligence. Compositional semantic models such as Compositional Distributional Semantics (DisCoCat) offer solutions by generalising vectors to tensors, but suffer from scaling bottlenecks when learning the tensors. Mapping DisCoCat onto Variational Quantum Circuits (VQCs) resolves this limitation for text, yet the methodology has not been expanded to multimodal situations such as the ones involved in CoCoGen. This paper introduces Mu-DisCoCat: a multimodal variational quantum learning framework for DisCoCat ...
| Authors | Mina Abbaszadeh, Matilda Karabina Moore, Raem Haq et al. |
|---|---|
| Primary category | cs.LG |
| Published | 6 October 2026 |
| Last updated at source | 6 October 2026 |
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