MM-EUREKA has achieved significant breakthroughs in three key dimensions:
- The Data Efficiency Revolution
With the rule-reinforced learning framework, only 54K graphical data are needed to achieve the performance of traditional models with millions of data, and the training cost is reduced by about 95% - Reasoning Paradigm Innovation
pull into,cap (a poem)<answer>Labeling mechanisms that allow the model to show the reasoning process in steps (e.g., geometry problems will calculate the radius before finding the area) - Dynamic reflective capacity
When a low confidence answer is detected, the image rechecking process is automatically triggered, similar to human error checking behavior
Practical tests show that MM-Eureka-Zero-38B improves the accuracy by 12.7% over the same-sized model in the MathVista benchmark test, especially in the complex topics that require graphical cross-validation.
This answer comes from the articleMM-EUREKA: A Multimodal Reinforcement Learning Tool for Exploring Visual ReasoningThe
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