DeFacto: Natural Language Generation from Natural Interactions
DeFacto is a dataset containing human demonstrations and feedback for improving the factual consistency of text summarization.
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.
DeFacto is a dataset containing human demonstrations and feedback for improving the factual consistency of text summarization.
CityLife is a flexible, high-fidelity simulation that allows users to define complex scenarios with essentially unlimited actors, including both pedestrians and vehicles. This tool allows each vehicle and pedestrian to operate with basic intelligence that…
TorchScale is a PyTorch library that allows researchers and developers to scale up Transformers efficiently and effectively. It has the implementation of fundamental research to improve modeling generality and capability as well as training stability…
The MoCapAct dataset contains training data and models for humanoid locomotion research. It consists of expert policies that are trained to track individual clip snippets and HDF5 files of noisy rollouts collected from each expert,…
This repository hosts the code release for the paper “Orchestrated Value Mapping for Reinforcement Learning”, published at ICLR 2022. This work was done by Mehdi Fatemi (Microsoft Research) and Arash Tavakoli (Max Planck Institute for…
Yardl is a simple schema language and command-line tool that generates domain types and serialization code. This is a tool for generating code based on a schema for raw instrument data.
This repository contains code for a series of research projects on Automated Reinforcement Learning (AutoRL).
The Damage Assessment Visualizer leverages satellite imagery from a disaster region to visualize conditions of building and structures before and after a disaster. It includes a visual layer on top of the satellite images which…
This is a lightweight web-interface for creating and sharing vector annotations over satellite/aerial imagery scenes.
Scikit-learn friendly library to interpret, and prompt-engineer text datasets using large language models.