Finally, in order to process long sequences, Xie et al. (2019) and Joshi et al. (2019) investigate simple approaches of truncating or partitioning them into smaller sequences, e.g., to fit within 512 token limit of BERT for classification; However, such partitioning leads to a loss of discriminative cross-partition information and is still computationally inefficient
table 4 shows data statistics of 5 datasets used in complementary + finetuning evaluation of our proposed topicBERt model via Document Classification task.