Visual Question Answering Breakthrough: How NoteMR Enhances Multimodal Model Reasoning

Breaking the Cognitive Boundaries of Visual Question Answering: How Knowledge and Visual Notes Enhance Multimodal Large Model Reasoning Introduction: The Cognitive Challenges of Visual Question Answering In today’s information explosion era, visual question answering (VQA) systems need to understand image content and answer complex questions like humans. However, existing multimodal large language models (MLLMs) often face two core challenges when dealing with visual problems requiring external knowledge: 1.1 Limitations of Traditional Methods Traditional knowledge-based visual question answering (KB-VQA) methods mainly fall into two categories: Explicit retrieval methods: Rely on external knowledge bases but introduce noisy information Implicit LLM methods: Utilize …