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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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Neural Networks for Cross-lingual Negation Scope Detection ...
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Abstract:
Negation scope has been annotated in several English and Chinese corpora, and highly accurate models for this task in these languages have been learned from these annotations. Unfortunately, annotations are not available in other languages. Could a model that detects negation scope be applied to a language that it hasn't been trained on? We develop neural models that learn from cross-lingual word embeddings or universal dependencies in English, and test them on Chinese, showing that they work surprisingly well. We find that modelling syntax is helpful even in monolingual settings and that cross-lingual word embeddings help relatively little, and we analyse cases that are still difficult for this task. ... : 8 pages ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://arxiv.org/abs/1810.02156 https://dx.doi.org/10.48550/arxiv.1810.02156
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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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