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README.md
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<p align="center">
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<b>Our Latest Innovations</b><br>
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<ul>
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<li><a href="https://www.marqo.ai/blog/introducing-marqtune">Embedding Fine-Tuning with
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<li><a href="https://www.marqo.ai/blog/search-model-for-fashion">FashionSigLIP</a>: Our latest model for fashion retrieval, combining cutting-edge techniques for enhanced search.</li>
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<li><a href="https://www.marqo.ai/blog/generalized-contrastive-learning-for-multi-modal-retrieval-and-ranking?_gl=1*vkeuqm*_gcl_au*MTM0OTc4OTY4Ny4xNzIzNTQ0NTcy">Generalized Contrastive Learning (GCL)</a>: A framework for training robust embedding models for multimodal search. <a href="https://arxiv.org/abs/2404.08535">Read the GCL paper on arXiv.</a></li>
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<li><a href="https://www.marqo.ai/blog/understanding-recall-in-hnsw-search">Understanding Recall in HNSW</a>: Insights into understanding and optimizing recall when using hierarchical navigable small worlds (HNSW) in vector search. <a href="https://arxiv.org/abs/2405.17813">Read the HNSW paper on arXiv.</a></li>
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<p align="center">
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<b>Our Latest Innovations</b><br>
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<ul>
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<li><a href="https://www.marqo.ai/blog/introducing-marqtune">Embedding Fine-Tuning with MarqTune</a>: Tailor embeddings to your domain for superior search results.</li>
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<li><a href="https://www.marqo.ai/blog/search-model-for-fashion">FashionSigLIP</a>: Our latest model for fashion retrieval, combining cutting-edge techniques for enhanced search.</li>
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<li><a href="https://www.marqo.ai/blog/generalized-contrastive-learning-for-multi-modal-retrieval-and-ranking?_gl=1*vkeuqm*_gcl_au*MTM0OTc4OTY4Ny4xNzIzNTQ0NTcy">Generalized Contrastive Learning (GCL)</a>: A framework for training robust embedding models for multimodal search. <a href="https://arxiv.org/abs/2404.08535">Read the GCL paper on arXiv.</a></li>
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<li><a href="https://www.marqo.ai/blog/understanding-recall-in-hnsw-search">Understanding Recall in HNSW</a>: Insights into understanding and optimizing recall when using hierarchical navigable small worlds (HNSW) in vector search. <a href="https://arxiv.org/abs/2405.17813">Read the HNSW paper on arXiv.</a></li>
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