New training method boosts AI multimodal reasoning with smaller, smarter datasets
Researchers at MiroMind AI and several Chinese universities have released OpenMMReasoner, a new training framework that improves the capabilities of language models in multimodal reasoning. The framework uses a two-stage process. It first refines a base model with a curated dataset in a supervised fine-tuning (SFT) stage. Then, a reinforcement learning (RL) stage guides the …
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