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Found 5 papers, 2 papers with code
Self-Training for Unsupervised Parsing with PRPN
To be able to use our model's predictions during training, we extend a recent neural UP architecture, the PRPN (Shen et al., 2018a) such that it can be trained in a semi-supervised fashion.
BLiMP: The Benchmark of Linguistic Minimal Pairs for English
We introduce The Benchmark of Linguistic Minimal Pairs (shortened to BLiMP), a challenge set for evaluating what language models (LMs) know about major grammatical phenomena in English.
Neural Unsupervised Parsing Beyond English
Recently, neural network models which automatically infer syntactic structure from raw text have started to achieve promising results.
Investigating BERT's Knowledge of Language: Five Analysis Methods with NPIs
We conclude that a variety of methods is necessary to reveal all relevant aspects of a model's grammatical knowledge in a given domain.
