Quantum Models with Multi-Stage Training for Compositional Concept Generalization
Compositional Concept Generalization (CoCoGen), the ability to systematically recombine learned primitives in novel contexts, is a key challenge for multimodal learning. In this work, we provide a solution using a compositional model of meaning that separates nouns from relations and uses tensors and variational quantum circuits to train them on data. This model enables us to employ a multi stage training paradigm, one that first learns object representations from single-object image-caption pairs, then subsequently transfers these to the relational stage where object parameters are frozen and optimisation is only applied to relational components. This design explicitly enforces compositi...
| Authors | Mina Abbaszadeh, Matilda Karabina Moore, Mehrnoosh Sadrzadeh et al. |
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| Primary category | cs.LG |
| Published | 16 August 2026 |
| Last updated at source | 16 August 2026 |
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