Exploring BGE-M3 and Splade: Two Machine Learning Models for Generating Sparse Embeddings

In my previous blog, we explored the evolution of information retrieval techniques from simple keyword matching to sophisticated context understanding and introduced the concept that sparse embeddings can be "learned." These clever embeddings merge the strengths of both dense and sparse retrieval methods. Learned sparse embeddings address the typical out-of-domain issues prevalent in dense retrieval and enhance traditional sparse methods by integrating contextual information.

Given the numerous benefits of learned sparse embeddings, you might wonder what models generate them …

ai blog concept context embeddings evolution information machine machine learning machinelearning machine learning models merge retrieval simple understanding vectordatabase