139 citations · 307 across the 29 of their papers we have counts for
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cs.CL2018
Can You Tell Me How to Get Past Sesame Street? Sentence-Level Pretraining Beyond Language Modeling
Alex Wang, Jan Hula, Patrick Xia +13
Natural language understanding has recently seen a surge of progress with the use of sentence encoders like ELMo (Peters et al., 2018a) and BERT (Devlin et al., 2019) which are pre…
cs.CL2018
RNNs Implicitly Implement Tensor Product Representations
R. Thomas McCoy, Tal Linzen, Ewan Dunbar +1
Recurrent neural networks (RNNs) can learn continuous vector representations of symbolic structures such as sequences and sentences; these representations often exhibit linear regu…
cs.CL2018
Non-entailed subsequences as a challenge for natural language inference
R. Thomas McCoy, Tal Linzen
Neural network models have shown great success at natural language inference (NLI), the task of determining whether a premise entails a hypothesis. However, recent studies suggest…