OpenView: Enhancing MLLMs with Out-of-View Visual Question Answering

This research explores enhancing Multimodal Large Language Models (MLLMs) with out-of-view Visual Question Answering (VQA) capabilities, indicating a focus on expanding the context MLLMs can utilize. The study's potential lies in improving the ability of AI to reason and answer questions about information beyond the immediately visible.

• •Focuses on out-of-view VQA for MLLMs.
• •Aims to improve AI reasoning based on broader visual contexts.
• •Research is likely from ArXiv, suggesting a novel approach.