Quantum Entangled Multimodal Fusion Networks (QEMFN): Resource-Aware Hybrid Vision-Language Fusion via Trainable Entanglement
cs.AI, quant-ph
Submitted: 2026-10-06
Updated: 2026-10-06
Terminology
Sources
- VisualBERT: A Simple and Performant Baseline for Vision and Language
- Align before Fuse: Vision and Language Representation Learning with Momentum Distillation
- BLIP: Bootstrapping Language-Image Pre-training for Unified Vision-Language Understanding and Generation
- ViLT: Vision-and-Language Transformer Without Convolution or Region Supervision
- LXMERT: Learning Cross-Modality Encoder Representations from Transformers
- UNITER: UNiversal Image-TExt Representation Learning
- PennyLane: Automatic differentiation of hybrid quantum-classical computations
- Quantum Multimodal Contrastive Learning Framework
- Microsoft COCO: Common Objects in Context
- Barren plateaus in quantum neural network training landscapes
- Representation Learning with Contrastive Predictive Coding
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