37 Things I Learned About Information Retrieval in Two Years at a Vector Database Company – Leonie Monigatti
From BM25 to RAG: Everything I learned about vector databases, embedding models, and vector search - and everything in between.
Vector Search
Training and Finetuning Sparse Embedding Models with Sentence Transformers v5
We’re on a journey to advance and democratize artificial intelligence through open source and open science.
Fine-Tuning
More efficient multi-vector embeddings with MUVERA | Weaviate
Weaviate `1.31` implements the MUVERA encoding algorithm for multi-vector embeddings. In this blog, we dive the algorithm in detail, including what MUVERA is, how it works, and whether it might make sense for you.
recipes/weaviate-features/multi-vector/reason_moderncolbert_comparison.ipynb at main · weaviate/recipes
This repository shares end-to-end notebooks on how to use various Weaviate features and integrations! - weaviate/recipes
Reason ModernColBertrecipes/weaviate-features/multi-vector/multi-vector-colipali-rag.ipynb at main · weaviate/recipes
This repository shares end-to-end notebooks on how to use various Weaviate features and integrations! - weaviate/recipes
Multimodal RAG
Cohere Embed v4 - Getting started - PDF Search.ipynb - Colab
Colab notebook
Multi-vector embeddings (ColBERT, ColPali, etc.) | Weaviate
Learn how to use multi-vector embeddings in Weaviate.
cohere-developer-experience/notebooks/guides/embed-v4-pdf-search/embed-v4-pdf-search.ipynb at main · cohere-ai/cohere-developer-experience
Docs, Snippets, Guides. Contribute to cohere-ai/cohere-developer-experience development by creating an account on GitHub.
RAG
Relevance Feedback in Informational Retrieval
Relerance feedback: from ancient history to LLMs Why relevance feedback techniques are good on paper but not popular in neural search and what we can do about it
Evaluating Chunking Strategies for Retrieval | Chroma Research
Do you know the answer to these three questions? You should... 1. What are vector embeddings and embedding models? 2. What’s the benefit of having a vector database for vector search? 3. What’s on the next horizon for AI applications? I just finished a 3-part webinar series… pic.twitter.com/nFOAPHQw2q— Victoria Slocum (@victorialslocum) March 5, 2025
Vector StoreMulti-vector embeddings (ColBERT, ColPali, etc.) | Weaviate
Learn how to use multi-vector embeddings in Weaviate.
Vector Stores - LlamaIndex
ColPali is changing the game for PDF retrieval by eliminating the need for OCR and chunking methods 🚀
Inspired by ColBERT’s success with text, ColPali splits an image of a document into patches, which are then processed through a vision LLM called PaliGemma. The embeddings for…
— Victoria Slocum (@victorialslocum)