Projects
High-stakes decision-making in areas like healthcare, finance and governance requires accountability for decisions and for how data is used in making decisions. Many concerns have been raised about whether machine learning (ML) models can meet these expectations. In many cases,…
xtreme classification is a rapidly growing research area in computer vision focusing on multi-class and multi-label problems involving an extremely large number of labels (ranging from thousands to billions).
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Large Language Models meet Program Synthesis Large pre-trained language models such as GPT-3, Codex, and Google’s language model are now capable of generating code from natural language specifications of programmer intent. We view these developments with a mixture of optimism…
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The goal of Project LITMUS is to discover strategies to evaluate massive multilingual models and also suggest data collection and training strategies to improve the performance of these models.
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Social science research into the impacts of digital technologies on society, politics, and culture in India
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Blockene is a new blockchain architecture that reduces resource usage at member nodes by orders of magnitude, requiring only a smartphone to participate in block validation and consensus. Despite being lightweight, Blockene provides high throughput and scales to millions of…
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The goal of Project Mélange is to understand the uses of and build tools around code-mixing, analyze and understand code-switching behavior, and equip speech and language processing systems with the capabilities of processing, understanding and generating code-switched language.
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MSR has a strong group of scientists working on algorithm design, analysis, and experimental evaluation, as well as researchers in related areas (e.g., coding theory), but no formal algorithms group. The Virtual Algorithms Center (VIRAL) brings these individuals together. The…
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Yogi is a research project within the Rigorous Software Engineering group at Microsoft Research India on software property checking. Our goal is to build a scalable software property checker by systematically combining static analysis with testing.