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Current MLLMs still struggle to connect the dots between images and text when they're interleaved, highlighting a critical gap in real-world multimodal understanding.
Fine-tuning smaller reasoning models on data from larger models can backfire spectacularly unless you carefully match the stylistic nuances of the student.
