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Hits 101 – 120 of 163

101
Pareto Probing: Trading Off Accuracy for Complexity
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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102
Speakers Fill Lexical Semantic Gaps with Context
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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103
Predicting Declension Class from Form and Meaning
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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104
The Paradigm Discovery Problem
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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105
A Tale of a Probe and a Parser
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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106
A Corpus for Large-Scale Phonetic Typology
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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107
Phonotactic Complexity and Its Trade-offs
In: Transactions of the Association for Computational Linguistics, 8 (2020)
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108
Exploring the Linear Subspace Hypothesis in Gender Bias Mitigation
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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109
If beam search is the answer, what was the question?
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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110
Intrinsic Probing through Dimension Selection
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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111
Information-Theoretic Probing for Linguistic Structure
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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112
It’s Easier to Translate out of English than into it: Measuring Neural Translation Difficulty by Cross-Mutual Information
In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (2020)
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113
Metaphor Detection Using Context and Concreteness
In: Proceedings of the Second Workshop on Figurative Language Processing (2020)
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114
Morphologically Aware Word-Level Translation
In: Proceedings of the 28th International Conference on Computational Linguistics (2020)
Abstract: We propose a novel morphologically aware probability model for bilingual lexicon induction, which jointly models lexeme translation and inflectional morphology in a structured way. Our model exploits the basic linguistic intuition that the lexeme is the key lexical unit of meaning, while inflectional morphology provides additional syntactic information. This approach leads to substantial performance improvements—19% average improvement in accuracy across 6 language pairs over the state of the art in the supervised setting and 16% in the weakly supervised setting. As another contribution, we highlight issues associated with modern BLI that stem from ignoring inflectional morphology, and propose three suggestions for improving the task.
URL: https://doi.org/10.3929/ethz-b-000462302
https://hdl.handle.net/20.500.11850/462302
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115
UniMorph 3.0: Universal Morphology
In: Proceedings of the 12th Language Resources and Evaluation Conference (2020)
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116
Morphologically Aware Word-Level Translation ...
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117
Pareto Probing: Trading Off Accuracy for Complexity ...
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118
A Tale of a Probe and a Parser ...
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119
A Tale of a Probe and a Parser ...
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120
UniMorph 3.0: Universal Morphology ...
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