One of the most remarkable and innovative features of MM-EUREKA is its Visual Reflection feature. This technology, through a special architectural design, enables the model to perform multiple rounds of thinking like a human during the reasoning process.
For specific implementation, the model will re-evaluate the initial inference results, focusing on reviewing important visual cues in the image. Test cases show that for complex tasks such as math application problems, the model will output a step-by-step reasoning process via tags, including multiple validations of visual elements such as area calculation and graph recognition.
This feature is especially reflected in the test_reflection.py test script, when dealing with geometric proof questions, the model will repeatedly confirm the key information such as angle relationship and length scale in the graph, and finally give the precise answer through the tag. This working mechanism dramatically improves the accuracy of answers to complex visual problems.
This answer comes from the articleMM-EUREKA: A Multimodal Reinforcement Learning Tool for Exploring Visual ReasoningThe
