Microsoft Technology Licensing, LLC

Shima Imani

Harsh Shrivastava

Liang Du

Disclosed are techniques for an AI system with a large language mode (LLM) with improved accuracy and reliability in solving mathematical problems. An initial query is transformed into a template query by replacing the original input values with variables. Multiple prompts are sent to the LLM, each being different from one another, and contextually related to the template query. Multiple results are responsively received from the LLM, each result including an analytical expression to solve the mathematical problem. Each of the expressions is evaluated using a numerical evaluation tool with variables of the expression being assigned a common set of randomly sampled values. A consensus is achieved when the evaluated expressions satisfy a consensus condition, such as when all outputs match consistently over N experiments or trials. After the consensus condition is reached, the original inputs are evaluated with one or more of the expressions, and the solution is output.

Mathematical reasoning using large language models

This disclosure relates to a time series segmentation system that efficiently and accurately segments univariate time series data. For example, the time series segmentation system utilizes proxy variable time series to identify distinct segments in a univariate time series. To illustrate, the time series segmentation system generates proxy variables that approximate a univariate time series and combine with the time series to generate a supplemented multivariate time series. The time series segmentation system then divides the supplemented multivariate time series into portions using time-based windows, converts the windowed subsequences into graph objects using a sparse graph recovery model, utilizes a conditional similarity model to determine segmentation timestamps from the graph objects, and generates a segmented univariate time series from the segmentation timestamps.

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Sammamish, WA, United States of America

Shima Imani