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Intrinsic Bias Metrics Do Not Correlate with Application Bias ...
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Inflecting when there's no majority: Limitations of encoder-decoder neural networks as cognitive models for German plurals ...
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Understanding and generating language with abstract meaning representation
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On understanding character-level models for representing morphology
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Methods for morphology learning in low(er)-resource scenarios
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Modelling speaker adaptation in second language learner dialogue
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Semantic Graph Parsing with Recurrent Neural Network DAG Grammars ...
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Fast machine translation on parallel and massively parallel hardware
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Learning natural language interfaces with neural models
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Dong, Li. - : The University of Edinburgh, 2019
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Indicatements that character language models learn English morpho-syntactic units and regularities ...
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Abstract:
Character language models have access to surface morphological patterns, but it is not clear whether or how they learn abstract morphological regularities. We instrument a character language model with several probes, finding that it can develop a specific unit to identify word boundaries and, by extension, morpheme boundaries, which allows it to capture linguistic properties and regularities of these units. Our language model proves surprisingly good at identifying the selectional restrictions of English derivational morphemes, a task that requires both morphological and syntactic awareness. Thus we conclude that, when morphemes overlap extensively with the words of a language, a character language model can perform morphological abstraction. ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/1809.00066 https://dx.doi.org/10.48550/arxiv.1809.00066
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Neural Networks for Cross-lingual Negation Scope Detection ...
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Understanding Learning Dynamics Of Language Models with SVCCA ...
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Entity-based coherence in statistical machine translation: a modelling and evaluation perspective
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Computational models for multilingual negation scope detection
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