✨Let Multimodal Embedders Learn When to Augment Query via Adaptive Query Augmentation
📝 Summary:
M-Solomon is a multimodal embedder that adaptively decides when to augment queries. It uses a Multimodal LLM to generate augmentations for queries that require them, learning to augment only when necessary. This approach improves performance and significantly reduces embedding latency compared to...
🔹 Publication Date: Published on Nov 4
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.02358
• PDF: https://arxiv.org/pdf/2511.02358
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For more data science resources:
✓ https://t.iss.one/DataScienceT
#MultimodalAI #LLM #Embeddings #MachineLearning #DeepLearning
📝 Summary:
M-Solomon is a multimodal embedder that adaptively decides when to augment queries. It uses a Multimodal LLM to generate augmentations for queries that require them, learning to augment only when necessary. This approach improves performance and significantly reduces embedding latency compared to...
🔹 Publication Date: Published on Nov 4
🔹 Paper Links:
• arXiv Page: https://arxiv.org/abs/2511.02358
• PDF: https://arxiv.org/pdf/2511.02358
==================================
For more data science resources:
✓ https://t.iss.one/DataScienceT
#MultimodalAI #LLM #Embeddings #MachineLearning #DeepLearning