Dataset Source Code
Raha: Failure analysis of a production WAN
Raha (MetaOpt) uses our open-source heuristic analyzer to quantify the impact of failures on a traffic engineered WAN.
Researcher Tools: code, datasets, & models
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.
Dataset Source Code
Implicit Language Models are RNNs
Implicit Language models are language models that calculate their outputs as a fixed-point iteration rather than a single forward pass. Implicit models offer increased representational power compared to transformers as we show in the accompanying…
Dataset Source Code
HORIZON: A Benchmark for in-the-wild User Behavior Modeling
This repository provides the code to construct the HORIZON benchmark — a large-scale, cross-domain benchmark built by refactoring the popular Amazon-Reviews 2023 dataset for evaluating sequential recommendation and user behavior modeling. We do not release…
Dataset Source Code
MarkItDown
MarkItDown is a lightweight Python utility for converting various files to Markdown for use with LLMs and related text analysis pipelines. To this end, it is most comparable to textract, but with a focus on…
Dataset Source Code
Code Release for Reprompting: Automated Chain-of-Thought Prompt Inference Through Gibbs Sampling
We introduce Reprompting, an iterative sampling algorithm that automatically learns the Chain-of-Thought (CoT) recipes for a given task without human intervention. Through Gibbs sampling, Reprompting infers the CoT recipes that work consistently well for a…
Dataset Source Code
fLSA: Learning Semantic Structures in Document Collections Using Foundation Models
Humans can learn to solve new tasks by inducing high-level strategies from example solutions to similar problems and then adapting these strategies to solve unseen problems. Can we use large language models to induce such…
Tool
Magma
Magma is a multimodal foundation model designed to both understand and act in digital and physical environments. Magma builds on the foundation models paradigm that pretraining on a larger amount of more diverse datasets allows…
Dataset Source Code
OG-RAG
OG-RAG enhances Large Language Models (LLMs) with domain-specific ontologies for improved factual accuracy and contextually relevant responses in fields with specialized workflows like agriculture, healthcare, knowledge work, and more. Paper: OG-RAG: Ontology-Grounded Retrieval-Augmented Generation For…
Dataset Source Code
CollabLLM: teaching LLMs to be more effective collaborators
Large Language Models are typically trained with next-turn rewards, limiting their ability to optimize for long-term interaction. As a result, they often respond passively to ambiguous or open-ended user requests, failing to help users reach…
Dataset Source Code
DSP+: Reviving DSP for Advanced Theorem Proving in the Era of Reasoning Models
Recent advancements, such as DeepSeek-Prover-V2-671B and Kimina-Prover-Preview-72B, demonstrate a prevailing trend in leveraging reinforcement learning (RL)-based large-scale training for automated theorem proving. Surprisingly, we discover that even without any training, careful neuro-symbolic coordination of existing…