Designed for evaluating the performance of large models on multimodal physics problems, PhysUniBenchmark provides a complete evaluation process and standardized testing framework. The tool's built-in evaluation scripts automatically feed questions into the model, collect answers and generate detailed evaluation reports. These reports contain accuracy, error analysis, and performance statistics for the model across different physics domains.
The evaluation system supports a variety of mainstream large models, including open-source models such as GPT-4o and LLaVA, and users can choose the appropriate model for testing according to their needs. The standardized evaluation method of the tool can objectively compare the performance differences of different models on the same physical problem, providing a reliable basis for model improvement.
The evaluation results also support visual presentation, with bar charts and line graphs automatically generated through scripts to visualize the differences in model performance across physical domains.
This answer comes from the articlePhysUniBenchmark: benchmarking tool for multimodal physics problemsThe
