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.
Uncertainty-aware self-training (UST) for few-shot text classification with pre-trained language models. With only 20-30 labeled samples per class for each task, UST can perform similar to fully supervised pre-trained language models like BERT fine-tuned on…
This self-hosted service developed for Azure, including its orchestration engine and security tools (including MSR’s RESTler), enables developers to embed security tooling into their CI/CD workflows.
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RESTler is the first stateful REST API fuzzing tool for automatically testing cloud services through their REST APIs and finding security and reliability bugs in these services.
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Microsoft.Recognizers.Text provides robust recognition and resolution of entities like numbers, units, and date/time; expressed in multiple languages. Full support for Chinese, English, French, Spanish, Portuguese, German, Italian, Turkish, and Hindi. Partial support for Dutch, Japanese,…
The iBox (Internet in a Box) project is an ongoing effort at Microsoft Research India on enabling data-informed network simulation. Currently, we use data in the form of per-packet traces gathered at senders and receivers…
This is a ROS wrapper for the Azure Spatial Anchors Linux SDK, allowing robots (and other devices equipped with a vision-based sensors and a pose estimation system) to create and query Azure Spatial Anchors, allowing…
Implementation of “Debiasing Item-to-Item Recommendations With Small Annotated Datasets” (RecSys ’20)
rankerEval – a Python library for evaluating rankings. A fast numpy-based implementation of ranking metrics for information retrieval and recommendation.
