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1
Incorporating Constituent Syntax for Coreference Resolution ...
Jiang, Fan; Cohn, Trevor. - : arXiv, 2022
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2
PPT: Parsimonious Parser Transfer for Unsupervised Cross-Lingual Adaptation ...
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3
Fairness-aware Class Imbalanced Learning ...
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4
As Easy as 1, 2, 3: Behavioural Testing of NMT Systems for Numerical Translation ...
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5
Putting words into the system's mouth: A targeted attack on neural machine translation using monolingual data poisoning ...
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6
It Is Not As Good As You Think! Evaluating Simultaneous Machine Translation on Interpretation Data ...
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7
Generating Diverse Descriptions from Semantic Graphs ...
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8
Balancing out Bias: Achieving Fairness Through Training Reweighting ...
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9
ChEMU 2020: Natural Language Processing Methods Are Effective for Information Extraction From Chemical Patents
In: Front Res Metr Anal (2021)
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10
Learning Coupled Policies for Simultaneous Machine Translation using Imitation Learning ...
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11
Please Mind the Root: Decoding Arborescences for Dependency Parsing
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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12
Measuring the Similarity of Grammatical Gender Systems by Comparing Partitions
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
Abstract: A grammatical gender system divides a lexicon into a small number of relatively fixed grammatical categories. How similar are these gender systems across languages? To quantify the similarity, we define gender systems extensionally, thereby reducing the problem of comparisons between languages’ gender systems to cluster evaluation. We borrow a rich inventory of statistical tools for cluster evaluation from the field of community detection (Driver and Kroeber, 1932; Cattell, 1945), that enable us to craft novel information theoretic metrics for measuring similarity between gender systems. We first validate our metrics, then use them to measure gender system similarity in 20 languages. We then ask whether our gender system similarities alone are sufficient to reconstruct historical relationships between languages. Towards this end, we make phylogenetic predictions on the popular, but thorny, problem from historical linguistics of inducing a phylogenetic tree over extant Indo-European languages. Of particular interest, languages on the same branch of our phylogenetic tree are notably similar, whereas languages from separate branches are no more similar than chance.
URL: https://hdl.handle.net/20.500.11850/462323
https://doi.org/10.3929/ethz-b-000462323
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13
Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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14
Learning a Cost-Effective Annotation Policy for Question Answering
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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15
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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16
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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17
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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18
Intrinsic Probing through Dimension Selection
In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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19
Control, Generate, Augment: A Scalable Framework for Multi-Attribute Text Generation
In: Findings of the Association for Computational Linguistics: EMNLP 2020 (2020)
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20
Textual Data Augmentation for Efficient Active Learning on Tiny Datasets
Sutcliffe, Richard; Samothrakis, Spyridon; Quteineh, Husam. - : Association for Computational Linguistics, 2020
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