Research
Discover an index of datasets, SDKs, APIs and open-source tools developed by Microsoft researchers and shared with the global academic community below. These experimental technologies—available through Azure AI Foundry Labs (opens in new tab)—offer a glimpse into the future of AI innovation.
SeerAttention is a learning-based method to enable block-level sparse attention for long-context LLM without using prefined static pattern or heuristic methods. It can be applied in Post-training or Fine-tuning stages. The Attention Gate units learn…
OmniParser is an advanced vision-based screen parsing module that converts user interface (UI) screenshots into structured elements, allowing agents to execute actions across various applications using visual data . By harnessing large vision-language model capabilities,…
This is the repository for paper “Causal integration of chemical structures in self-supervised learning improves representations of microscopy images for morphological profiling”. Learning effective representations of cells in microscopy images can fuel many applications. Here,…
ProtNote is a multimodal deep learning model that leverages free-form text to enable both supervised and zero-shot protein function prediction.
Automatically synthesize proof annotations that help Verus prove the correctness of Rust code.
This dataset is the Version 2.0 of the FStar Data Set. This dataset’s primary objective is to train and evaluate Proof-oriented Programming with AI (PoPAI, in short). Given a specification of a program and proof…
This dataset contains programs and proofs in F* proof-oriented programming language. The data, proposed in Towards Neural Synthesis for SMT-Assisted Proof-Oriented Programming, is an archive of source code, build artifacts, and metadata assembled from eight…
This is a codebase to perform privacy-preserving in-context learning with differentially private few-shot generation.
This repository contains the code for the Eureka ML Insights, a framework for standardizing evaluations of large foundation models, beyond single-score reporting and rankings. The framework is designed to help researchers and practitioners run reproducible evaluations…