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Frustratingly Simple but Surprisingly Strong: Using Language-Independent Features for Zero-shot Cross-lingual Semantic Parsing ...
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Please Mind the Root: Decoding Arborescences for Dependency Parsing
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In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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Measuring the Similarity of Grammatical Gender Systems by Comparing Partitions
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In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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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.
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URL: https://hdl.handle.net/20.500.11850/462323
https://doi.org/10.3929/ethz-b-000462323
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Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model
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In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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Learning a Cost-Effective Annotation Policy for Question Answering
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In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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Pareto Probing: Trading Off Accuracy for Complexity
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In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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Speakers Fill Lexical Semantic Gaps with Context
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In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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Exploring the Linear Subspace Hypothesis in Gender Bias Mitigation
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In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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Intrinsic Probing through Dimension Selection
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In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP) (2020)
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Textual Data Augmentation for Efficient Active Learning on Tiny Datasets
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LitCrit: exploring intentions as a basis for automated feedback on Related Work.
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Unsupervised stance detection for arguments from consequences
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XCOPA: A multilingual dataset for causal commonsense reasoning
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From zero to hero: On the limitations of zero-shot language transfer with multilingual transformers
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Inference in an Approach to Discourse Anaphora
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In: North East Linguistics Society (2020)
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A survey of cross-lingual features for zero-shot cross-lingual semantic parsing ...
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