Adding word-order and sentence-order reconstruction tasks to BERT pre-training improves performance on GLUE, SNLI, and SQuAD v1.1 benchmarks.
Word Ordering Without Syntax
1 Pith paper cite this work. Polarity classification is still indexing.
abstract
Recent work on word ordering has argued that syntactic structure is important, or even required, for effectively recovering the order of a sentence. We find that, in fact, an n-gram language model with a simple heuristic gives strong results on this task. Furthermore, we show that a long short-term memory (LSTM) language model is even more effective at recovering order, with our basic model outperforming a state-of-the-art syntactic model by 11.5 BLEU points. Additional data and larger beams yield further gains, at the expense of training and search time.
fields
cs.CL 1years
2019 1verdicts
CONDITIONAL 1representative citing papers
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StructBERT: Incorporating Language Structures into Pre-training for Deep Language Understanding
Adding word-order and sentence-order reconstruction tasks to BERT pre-training improves performance on GLUE, SNLI, and SQuAD v1.1 benchmarks.