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Language Models Use Monotonicity to Assess NPI Licensing ...
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Causal Transformers Perform Below Chance on Recursive Nested Constructions, Unlike Humans ...
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Sparse Interventions in Language Models with Differentiable Masking ...
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Mechanisms for Handling Nested Dependencies in Neural-Network Language Models and Humans ...
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Compositionality decomposed: how do neural networks generalise? ...
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Under the Hood: Using Diagnostic Classifiers to Investigate and Improve how Language Models Track Agreement Information ...
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Do Language Models Understand Anything? On the Ability of LSTMs to Understand Negative Polarity Items ...
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Abstract:
In this paper, we attempt to link the inner workings of a neural language model to linguistic theory, focusing on a complex phenomenon well discussed in formal linguis- tics: (negative) polarity items. We briefly discuss the leading hypotheses about the licensing contexts that allow negative polarity items and evaluate to what extent a neural language model has the ability to correctly process a subset of such constructions. We show that the model finds a relation between the licensing context and the negative polarity item and appears to be aware of the scope of this context, which we extract from a parse tree of the sentence. With this research, we hope to pave the way for other studies linking formal linguistics to deep learning. ... : Accepted to the EMNLP workshop "Analyzing and interpreting neural networks for NLP" ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.1808.10627 https://arxiv.org/abs/1808.10627
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