How Google’s Lang Extract Turns Messy Documents into Trustworthy JSON and Interactive HTML

Google’s Lang Extract uses prompts with Gemini or GPT, works locally or in the cloud, and helps you ship reliable, traceable data faster.
Le Lézard

MongoDB Sets a New Standard for Retrieval Accuracy with Voyage 4 Models for Production-Ready AI Applications

MongoDB, Inc. today announced an industry-first expansion of its AI capabilities at MongoDB.local San Francisco, bringing ...
IEEE

Zero-shot Learning with Minimum Instruction to Extract Social Determinants and Family History from Clinical Notes using GPT Model

Abstract: Demographics, social determinants of health, and family history documented in the unstructured text within the electronic health records are increasingly being studied to understand how this ...
GitHub

A Smol Conversation 0.2 Billion Smol Model (ChatLM-Smol-0.2B)

Today's large language models tend to have large parameters, and consumer-grade computers are slow to do simple inference, let alone train a model from scratch. The goal of this project is to organize ...
IEEE

Do Self-Supervised Speech and Language Models Extract Similar Representations as Human Brain?

Abstract: Speech and language models trained through self-supervised learning (SSL) demonstrate strong alignment with brain activity during speech and language perception. However, given their ...
GitHub

GLiREL : Generalist and Lightweight model for Zero-Shot Relation Extraction

GLiREL is a Relation Extraction model capable of classifying unseen relations given the entities within a text. This builds upon the excelent work done by Urchade Zaratiana, Nadi Tomeh, Pierre Holat, ...