
miniCOIL: on the Road to Usable Sparse Neural Retrieval
Introducing miniCOIL, a lightweight sparse neural retriever capable of generalization.
Evgeniya Sukhodolskaya
May 13, 2025
Explore the research behind modern embeddings and neural retrieval. Dive into sparse neural models, late interaction, metric learning, and new baselines for hybrid search.

Introducing miniCOIL, a lightweight sparse neural retriever capable of generalization.
Evgeniya Sukhodolskaya
May 13, 2025

A comprehensive guide to modern sparse neural retrievers: COIL, TILDEv2, SPLADE, and more. Find out how they work and learn how to use them effectively.
Evgeniya Sukhodolskaya
October 23, 2024

We recently discovered that embedding models can become late interaction models & can perform surprisingly well in some scenarios. See what we learned here.
Kacper Łukawski
August 14, 2024

Introducing BM42 - a new sparse embedding approach, which combines the benefits of exact keyword search with the intelligence of transformers.
Andrey Vasnetsov
July 01, 2024

What are the advantages of Triplet Loss over Contrastive loss and how to efficiently implement it?
Yusuf Sarıgöz
March 24, 2022

Practical recommendations on how to train a matching model and serve it in production. Even with no labeled data.
Andrei Vasnetsov
May 15, 2021
