The Death of Feature Engineering? BERT with Linguistic Features on SQuAD 2.0

arXiv:2404.03184v1 Announce Type: new
Abstract: Machine reading comprehension is an essential natural language processing task, which takes into a pair of context and query and predicts the corresponding answer to query. In this project, we developed an end-to-end question answering model incorporating BERT and additional linguistic features. We conclude that the BERT base model will be improved by incorporating the features. The EM score and F1 score are improved 2.17 and 2.14 compared with BERT(base). Our best single model reaches …

abstract arxiv bert context cs.ai cs.cl death engineering feature feature engineering features language language processing machine natural natural language natural language processing processing project query question question answering reading type