The GOLD model's approach of separately processing symbols and geometric primitives can be extended to other multimodal reasoning tasks by adapting the model's architecture and training process to suit the specific requirements of different tasks. Here are some ways this approach can be applied to other tasks:
Medical Image Analysis: In medical imaging, tasks often involve interpreting images alongside textual descriptions or medical records. By adapting the GOLD model to extract relations between medical images and corresponding text, it could assist in tasks like disease diagnosis, tumor detection, or treatment planning.
Robotics and Automation: In robotics, understanding the environment through both visual inputs and textual commands is crucial. By extending the GOLD model to handle relations between visual data from sensors and textual instructions, it could enhance robots' ability to perform complex tasks in varied environments.
Natural Disaster Response: During natural disasters, responders often need to analyze satellite imagery along with textual reports to assess the situation. The GOLD model's approach could be applied to extract relations between visual data and textual information to aid in disaster response efforts.
Financial Analysis: In finance, analyzing financial reports alongside visual data like graphs or charts is common. By adapting the GOLD model to handle relations between financial data and textual descriptions, it could assist in tasks like fraud detection, risk assessment, or investment analysis.
By customizing the model's input processing, relation extraction mechanisms, and output generation, the GOLD model's framework can be tailored to a wide range of multimodal reasoning tasks beyond geometry problem solving.