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Differentiable subset pruning of transformer heads
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In: Transactions of the Association for Computational Linguistics, 9 (2021)
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| 62 |
Parameter space factorization for zero-shot learning across tasks and languages
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In: Transactions of the Association for Computational Linguistics, 9 (2021)
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| 63 |
Disambiguatory Signals are Stronger in Word-initial Positions
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In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume (2021)
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| 64 |
Searching for More Efficient Dynamic Programs
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In: Findings of the Association for Computational Linguistics: EMNLP 2021 (2021)
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| 65 |
How (Non-)Optimal is the Lexicon?
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In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021)
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| 66 |
A Bayesian Framework for Information-Theoretic Probing
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In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
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| 67 |
Examining the Inductive Bias of Neural Language Models with Artificial Languages
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In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (2021)
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| 68 |
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs
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In: Transactions of the Association for Computational Linguistics, 9 (2021)
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| 71 |
Do Syntactic Probes Probe Syntax? Experiments with Jabberwocky Probing ...
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| 72 |
Do Syntactic Probes Probe Syntax? Experiments with Jabberwocky Probing ...
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| 76 |
Disambiguatory Signals are Stronger in Word-initial Positions ...
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| 77 |
Finding Concept-specific Biases in Form--Meaning Associations ...
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Abstract:
Read the paper on the folowing link: https://www.aclweb.org/anthology/2021.naacl-main.349/ Abstract: This work presents an information-theoretic operationalisation of cross-linguistic non-arbitrariness. It is not a new idea that there are small, cross-linguistic associations between the forms and meanings of words. For instance, it has been claimed (Blasi et al., 2016) that the word for "tongue" is more likely than chance to contain the phone [l]. By controlling for the influence of language family and geographic proximity within a very large concept-aligned, cross-lingual lexicon, we extend methods previously used to detect within language non-arbitrariness (Pimentel et al., 2019) to measure cross-linguistic associations. We find that there is a significant effect of non-arbitrariness, but it is unsurprisingly small (less than 0.5% on average according to our information-theoretic estimate). We also provide a concept-level analysis which shows that a quarter of the concepts considered in our work exhibit a ...
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Keyword:
Artificial Intelligence; Computer Science and Engineering; Intelligent System; Natural Language Processing; Psycholinguistics
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URL: https://underline.io/lecture/19655-finding-concept-specific-biases-in-form--meaning-associations
https://dx.doi.org/10.48448/gkde-dn79
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| 78 |
Backtranslation feedback improves user confidence in MT, not quality
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| 79 |
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs ...
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| 80 |
Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model ...
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