Vision-DeepResearch: Incentivizing DeepResearch Capability in Multimodal Large Language Models

1. 1Augment multimodal large language models with external knowledge sources
2. 2Implement 'reasoning-then-tool-call' approach for visual and textual search engines
3. 3Evaluate the model's performance on tasks requiring extensive factual information
4. 4Fine-tune the model to improve its deep research capability

Researchers and AI engineers working on multimodal large language models can benefit from this approach to improve the model's ability to conduct deep research and retrieve factual information

💡 Multimodal large language models can be improved by augmenting them with external knowledge sources and implementing a 'reasoning-then-tool-call' approach

🔍 Incentivize deep research in MLLMs with Vision-DeepResearch!