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Microsoft Research introduces GigaPath-Flash and GigaTIME-Flash, pathology foundation models that reportedly reduce computational demands while maintaining strong performance, enabling larger studies and broader exploration in computational pathology.
Microsoft Research introduced MindTopo, a new benchmark designed to test how vision-language models (VLMs) understand topological and spatial relationships. The announcement frames MindTopo as a tool to evaluate and guide improvements in spatial reasoning and planning capabilities of VLMs.
Microsoft Research published CARE-X, a research proposal for radiology vision-language models (VLMs) that combines auxiliary supervision, reward-aligned learning, and tool-augmented measurement to enable flexible reasoning, calibrated predictions, and measurement-based tools for chest X-ray interpretation.
Orchard is an open-source framework from Microsoft Research intended for the research community to train and evaluate AI agents across different task types. The project is presented as reducing infrastructure complexity and enabling reuse of the same tooling to support strong performance even with smaller models.
Microsoft Research describes Echoverse, an approach that trains computer-use AI agents in realistic, evolving environments instead of merely supplying more training tasks; the aim is to help agents handle multi-step workflows such as email and customer support. The post highlights improving agents as tasks, tests, and environments change rather than relying on static task sets.
Microsoft Research published a post about EvoLib, an approach that aims to convert accumulated experience into evolving knowledge by extracting reusable skills and insights to help LLMs learn and adapt across tasks after deployment. The post emphasizes that LLMs do not get smarter simply by remembering more, and positions EvoLib as a way to reuse experience for long-term adaptability.
Microsoft Research released Aurora 1.5, an update to the open Aurora foundation model that adds 22 additional variables, shifts to hourly temporal resolution, and introduces probabilistic ensemble forecasting to support weather, climate and energy applications. The changes are intended to make the model more useful for real-world Earth-system and operational use cases.
Microsoft Research introduced Flint, an open-source visualization language that aims to let AI agents generate expressive charts from compact, human-editable specifications, positioned as a middle path between terse chart specs and hand-crafted visualizations.
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