A Multi-level Neural Network for Implicit Causality Detection in Web Texts
TABLE VI: Performance of Different Word Embeddings.
['[BOLD] Type', '[BOLD] F1-score', '[BOLD] AUROC', '[BOLD] AUPRC']
Stability on Different Word Embeddings. As is well-known, BERT uses a word-piece algorithm to split words into sub-words, which is different from the pre-trained word embeddings used by MCDN and other models. Here we want to evaluate the impact of different word embeddings on the performance of MCDN.