223 citations · 849 across the 52 of their papers we have counts for
56 papers
Mu-DisCoCat: A Variational Pipeline for Compositional Generalization on Quantum Processors
Mina Abbaszadeh, Matilda Karabina Moore, Raem Haq +2
Achieving compositional concept generalization (CoCoGen), the ability to understand novel situations by recombining learned primitives, remains a fundamental challenge in artificia…
Quantum Models with Multi-Stage Training for Compositional Concept Generalization
Mina Abbaszadeh, Matilda Karabina Moore, Mehrnoosh Sadrzadeh +1
Compositional Concept Generalization (CoCoGen), the ability to systematically recombine learned primitives in novel contexts, is a key challenge for multimodal learning. In this wo…
DisCoCLIP: A Distributional Compositional Tensor Network Encoder for Vision-Language Understanding
Kin Ian Lo, Hala Hawashin, Mina Abbaszadeh +3
Recent vision-language models excel at large-scale image-text alignment but often neglect the compositional structure of language, leading to failures on tasks that hinge on word o…
Compositional Concept Generalization with Variational Quantum Circuits
Hala Hawashin, Mina Abbaszadeh, Nicholas Joseph +3
Compositional generalization is a key facet of human cognition, but lacking in current AI tools such as vision-language models. Previous work examined whether a compositional tenso…
Quantum-Like Contextuality in Large Language Models
Kin Ian Lo, Mehrnoosh Sadrzadeh, Shane Mansfield
Contextuality is a distinguishing feature of quantum mechanics and there is growing evidence that it is a necessary condition for quantum advantage. In order to make use of it, res…
Multimodal Structure-Aware Quantum Data Processing
Hala Hawashin, Mehrnoosh Sadrzadeh
While large language models (LLMs) have advanced the field of natural language processing (NLP), their "black box" nature obscures their decision-making processes. To address this,…