MM-EUREKA is an open source multimodal reasoning tool jointly developed by Shanghai Artificial Intelligence Laboratory, Shanghai Jiaotong University and other organizations, and its core innovation lies in extending rule-based reinforcement learning techniques to visual and text co-processing scenarios.
Key technical advantages include:
- Multi-modal fusion capability: Parsing of both image and text information, e.g., automatic correlation of graphical features and textual descriptions for math problems with graphs.
- Rule-driven reinforcement learning: Reduce data dependency with a structured training framework that can outperform traditional multi-million data models with 54K training samples.
- Visual Reflection Mechanism: mimic human 'epiphany' behavior during reasoning and support secondary validation of image cues
- dual-model architecture: Provide two parameter scales, 8B and 38B, to balance the efficiency and accuracy needs.
This answer comes from the articleMM-EUREKA: A Multimodal Reinforcement Learning Tool for Exploring Visual ReasoningThe
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