This repo provides the code for reproducing BoKA: an automatic knowledge amalgamation framework for identifying a combination that can learn a superior student model without human labor.
We use two multi-domain datasets:
- PubMedQA (You can download it from this link: https://github.com/pubmedqa/pubmedqa)
- MedMCQA (You can download it from this link: https://github.com/MedMCQA/MedMCQA)
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To automatically select combinations, conduct the plural KA process, and evaluate the produced student model, use the following commands:
python bo.py(for PubMedQA)python bo_medmcqa.py(for MedMCQA)
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We provide superior student models on PubMedQA and MedMCQA, respectively. (https://drive.google.com/drive/folders/1UKUfop1ZXm4_V70xIv_iS6ZNpJi5Scxi?usp=sharing) The evaluation commands are as follows:
python evaluate.py(for both PubMedQA and MedMCQA)