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Status: Unchecked ×Keyword: systematic generalization ×Clear all

2 claims from 1 paper

1. Computer Science › Natural Language Processing Techniques

   Neural Network Acceptability Judgments

   Warstadt, Singh and Bowman · Transactions of the Association for Computational Linguistics · 2019

   The paper introduces CoLA, a set of 10,657 English sentences labelled grammatical or ungrammatical, and tests how well neural networks judge acceptability, finding all models far below human level.

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   1. UncheckedRecurrent neural networks trained as baselines on the CoLA acceptability task scored better than the unsupervised models of Lau et al. (2016).“As baselines, we train several recurrent neural network models on acceptability classification, and find that our models outperform unsupervised models by Lau et al (2016) on CoLA.”
   2. UncheckedAll the neural network models tested performed far below human level on a wide range of grammatical constructions in judging sentence acceptability.“However, all models we test perform far below human level on a wide range of grammatical constructions.”