Background
Electromagnetics problems often involve complex concepts such as space vectors and field distributions, and are a generally low-scoring area in PhysUniBenchmark tests. The performance of the model can be significantly improved by special optimization.
procedure
- Data filtering
utilizationload_data.py --filter electromagnetismExtracting the EM Scholars dataset - error analysis
Running a post-evaluation viewresults/The error classification report under focuses on errors related to vector arithmetic and right-hand rule - Increased relevance
1. Add coordinate system annotations to the image (modify)preprocess.py(used form a nominal expression)add_coordinate()function)
2. Add Maxwell's system of equations mnemonic to the prompt
advanced program
For open-source models, recommendations:
1. Addition of the specialization attention layer of the Ampere's ring law to models such as LLaVA
2. Utilizationdata/augment/Expanding training data with the field line graph generator in the
This answer comes from the articlePhysUniBenchmark: benchmarking tool for multimodal physics problemsThe
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