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Chemical VLMs can achieve SOTA performance by prioritizing reasoning through fine-grained analysis of visual inputs, such as identifying functional groups, before generating answers.
Forget hand-annotated code: OmniDiagram uses a self-evolving visual interrogation technique to train diagram-generating AI, achieving state-of-the-art results.
