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.
This is the official repository of paper “Distilled Decoding 1: One-step Sampling of Image Auto-regressive Models with Flow Matching.” We propose Distilled Decoding (DD) to distill a pre-trained image auto-regressive model to few steps for…
This is the official code repository for the paper “Unearthing Skill-level Insights for Understanding Tradeoffs of Foundation Models”. All rationales, localized skills, and skill-slices for the 12 datasets studied in the paper can also be accessed…
This is the official codebase for the paper “The Belief State Transformer”, based on the nanoGPT repository by Andrej Karpathy.
debug-gym is a text-based interactive debugging framework, designed for debugging Python programs.
MatterGen is a generative model for inorganic materials design across the periodic table that can be fine-tuned to steer the generation towards a wide range of property constraints.
HeurAgenix is a novel framework based on LLM, designed to generate, evolve, evaluate, and select heuristic algorithms for solving combinatorial optimization problems. It leverages the power of large language models to autonomously handle various optimization…
MarS is a cutting-edge financial market simulation engine powered by the Large Market Model (LMM), a generative foundation model.
