A fully open pipeline that rewrites multimodal instruction data into CoT-style rationales yields a 12M dataset and an 8B model with strong benchmark gains, though some evaluation benchmarks overlap the training data.
- Instructions should require the responder to infer and utilize visual information that may not be explicitly stated in the instruction
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MAmmoTH-VL: Eliciting Multimodal Reasoning with Instruction Tuning at Scale
A fully open pipeline that rewrites multimodal instruction data into CoT-style rationales yields a 12M dataset and an 8B model with strong benchmark gains, though some evaluation benchmarks overlap the training data.