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Neural Domain Adaptation for Biomedical Question Answering

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Figure 1:Network architecture of our systemfor biomedical question answering. At its core,it uses an extractive neural QA system as a blackbox (we use FastQA (Weissenborn et al., 2017)).The embedding layer is modified in order to in-clude biomedical word em
Table 1: Comparison of various transfer learning techniques. In Experiment 1, the model was trained onBioASQ only
Table 2:Performance of a model ensemble.Five models have been trained on the BioASQ3Bdataset and tested on the 4B test questions
Table 3: Comparison to systems on last year’s (fourth) BioASQ challenge for factoid and list questions.For each batch and question type, we list the performance of the best competing system, our single modeland ensemble

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