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VLMs can now get a million-scale boost in chart-understanding abilities thanks to a new dataset with paired code, images, data, and reasoning.
Instead of forcing modalities to imitate each other, IIBalance lets each modality contribute according to its intrinsic information budget, leading to better multimodal fusion.
Forget hand-annotated data: ChartGen automatically generates 222.5K chart-image/code pairs, exposing surprising weaknesses in today's VLMs at reconstructing plotting scripts.
A new 2B parameter vision-language model, Granite Vision, rivals larger models on visual document understanding tasks while offering a transparent and commercially-friendly open-source license.
