par David Le Louarn | Sep 17, 2024 | Publications R&D
Context Grounded Question Answering (QA) is usually the last step of a RAG pipeline: given a question and a set of documents retrieved from the corpus, an LLM must generate an answer. We expect the LLM to cite which document each piece of information is coming from,...
par David Le Louarn | Sep 3, 2024 | Publications R&D
Using Vision LLMs + late interaction to improve document retrieval (RAG, search engines, etc.), solely using the image representation of document pages (paper)! Context To improve the query answering capabilities of LLMs, it is often best to first search for...
par David Le Louarn | Sep 3, 2024 | Publications R&D
Intro We are thrilled to introduce CroissantLLM, a small but capable 1.3 billion parameter language model trained on 3T tokens, that is fully open, and truly bilingual ! The goal is to bring to the research and industrial community a high-performance, fully...
