GitHub | Paper | Website
We-Math 2.0 is a unified system designed to comprehensively enhance the mathematical reasoning capabilities of Multimodal Large Language Models (MLLMs).
It integrates a structured mathematical knowledge system, model-centric data space modeling, and a reinforcement learning (RL)-based training paradigm to achieve both broad conceptual coverage and robust reasoning performance across varying difficulty levels.
The key… See the full description on the dataset page:
https://huggingface.co/datasets/We-Math/We-Math2.0-Standard.
