ReT-2
					Collection
				
Models and data for the paper "Recurrence Meets Transformers for Universal Multimodal Retrieval" (arXiv 2509.08897)
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Official implementation of ReT-2: Recurrence Meets Transformers for Universal Multimodal Retrieval.
This model features visual and textual backbones based on openai/clip-vit-base-patch32. 
The backbones have been fine-tuned on the M2KR dataset. 
@article{caffagni2025recurrencemeetstransformers,
      title={{Recurrence Meets Transformers for Universal Multimodal Retrieval}}, 
      author={Davide Caffagni and Sara Sarto and Marcella Cornia and Lorenzo Baraldi and Rita Cucchiara},
      journal={arXiv preprint arXiv:2509.08897},
      year={2025}
}
Base model
openai/clip-vit-base-patch32