ESsEN is a parameter-efficient two-tower vision-language transformer that matches larger models on discriminative tasks after training end-to-end with limited data and resources.
arXiv preprint arXiv:2307.03254 , year=
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A comprehensive survey of edge deep learning in computer vision and medical diagnostics that presents a novel categorization of hardware platforms by performance and usage scenarios.
The survey identifies a key tension in multilingual vision-language models between language neutrality via contrastive learning and cultural awareness via diverse data, with most benchmarks relying on translation-based evaluation.
citing papers explorer
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ESsEN: Training Compact Discriminative Vision-Language Transformers in a Low-Resource Setting
ESsEN is a parameter-efficient two-tower vision-language transformer that matches larger models on discriminative tasks after training end-to-end with limited data and resources.
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Edge Deep Learning in Computer Vision and Medical Diagnostics: A Comprehensive Survey
A comprehensive survey of edge deep learning in computer vision and medical diagnostics that presents a novel categorization of hardware platforms by performance and usage scenarios.
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Multilingual Vision-Language Models, A Survey
The survey identifies a key tension in multilingual vision-language models between language neutrality via contrastive learning and cultural awareness via diverse data, with most benchmarks relying on translation-based evaluation.
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