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.
Vidur is a high-fidelity and extensible LLM inference simulator. It can help you with capacity planning and finding the best deployment configuration for your LLM deployments, test new research ideas like new scheduling algorithms, optimizations…
PyTorch emulation library for Microscaling (MX)-compatible data formats
\psi (Platform for Situated Intelligence) is an open-source, extensible framework that accelerates development and research of multimodal, integrative AI systems. The platform consists of three layers. The Runtime layer provides a parallel programming model centered…
Official code for the paper published at EMNLP 2023 paper: Multilingual Evaluation of Generative AI (MEGA), a framework to evaluate Large Language Models (LLMs) on various multilingual benchmarks
Enable Next-Gen Large Language Model Applications. AutoGen is a framework that enables the development of LLM applications using multiple agents that can converse with each other to solve tasks. AutoGen agents are customizable, conversable, and…
A space simulation platform that caters to individuals with diverse research interests, including networking, AI, computing, and more. Unlike traditional simulators tied to specific research applications, our design allows for seamless integration of various space-related…
DSPDA: Differentially Private Synthetic Data via Foundation Model APIs—This repo is a Python library to generate differentially private (DP) synthetic data without the need of any ML model training. It is based on the following papers…
We study various aspects of our proposed model including, dependency on the number of eigencomponents utilized, latent polynomial filters learned, and performance of the individual polynomials on the node classification task. We further show that…