New training method boosts AI multimodal reasoning with smaller, smarter datasets
PositiveArtificial Intelligence
- Researchers at MiroMind AI and several Chinese universities have introduced OpenMMReasoner, a new training framework designed to enhance the multimodal reasoning capabilities of language models. This framework employs a two-stage process, refining a base model through supervised fine-tuning followed by reinforcement learning to improve reasoning in tasks that integrate text and visual data.
- The introduction of OpenMMReasoner is significant as it demonstrates that models trained with this framework can outperform leading visual reasoning models while utilizing smaller, higher-quality datasets. This advancement not only enhances AI capabilities but also provides an open-source foundation for developing robust applications requiring traceability.
— via World Pulse Now AI Editorial System
