One primary driver for artificial intelligence research in mathematical reasoning is that it may further increase model understanding and problem-solving abilities on complex mathematical problems.

Math-OCR-Zero is based on the VeRL framework and leverages the synthetic OCR-Math dataset to enhance the reasoning capabilities of multimodal large models. It serves as a reproduction of ...

Language models have made significant strides in mathematical reasoning, with synthetic data playing a crucial role in their development. However, the field faces significant challenges due to the ...

The training steps of the model include 2 stages: Continue pretraining: Using text corpus collected from external data about elementary school mathematics knowledge, some types of exercises to help ...

Abstract: We present a multi-way parallel corpus of Math Word Problems (MWPs) in nine languages, including six low-resource languages. To date, this is the largest multilingual MWP dataset available.

Mathematics has always posed a significant challenge for AI models. Mastering math requires complex reasoning skills, and for AI, this task is anything but straightforward. That creates a huge problem ...

Mathematics is the foundation of countless sciences, allowing us to model things like planetary orbits, atomic motion, signal frequencies, protein folding, and more. Moreover, it’s a valuable testbed ...