61 |
Differentiable subset pruning of transformer heads
|
|
|
|
In: Transactions of the Association for Computational Linguistics, 9 (2021)
|
|
BASE
|
|
Show details
|
|
62 |
Parameter space factorization for zero-shot learning across tasks and languages
|
|
|
|
In: Transactions of the Association for Computational Linguistics, 9 (2021)
|
|
BASE
|
|
Show details
|
|
63 |
Disambiguatory Signals are Stronger in Word-initial Positions
|
|
|
|
In: Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume (2021)
|
|
BASE
|
|
Show details
|
|
64 |
Searching for More Efficient Dynamic Programs
|
|
|
|
In: Findings of the Association for Computational Linguistics: EMNLP 2021 (2021)
|
|
BASE
|
|
Show details
|
|
65 |
How (Non-)Optimal is the Lexicon?
|
|
|
|
In: Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (2021)
|
|
BASE
|
|
Show details
|
|
66 |
A Bayesian Framework for Information-Theoretic Probing
|
|
|
|
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing (2021)
|
|
BASE
|
|
Show details
|
|
67 |
Examining the Inductive Bias of Neural Language Models with Artificial Languages
|
|
|
|
In: Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (2021)
|
|
BASE
|
|
Show details
|
|
68 |
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs
|
|
|
|
In: Transactions of the Association for Computational Linguistics, 9 (2021)
|
|
BASE
|
|
Show details
|
|
71 |
Do Syntactic Probes Probe Syntax? Experiments with Jabberwocky Probing ...
|
|
|
|
BASE
|
|
Show details
|
|
72 |
Do Syntactic Probes Probe Syntax? Experiments with Jabberwocky Probing ...
|
|
|
|
BASE
|
|
Show details
|
|
76 |
Disambiguatory Signals are Stronger in Word-initial Positions ...
|
|
|
|
BASE
|
|
Show details
|
|
77 |
Finding Concept-specific Biases in Form--Meaning Associations ...
|
|
|
|
BASE
|
|
Show details
|
|
78 |
Backtranslation feedback improves user confidence in MT, not quality
|
|
|
|
BASE
|
|
Show details
|
|
79 |
On the Relationships Between the Grammatical Genders of Inanimate Nouns and Their Co-Occurring Adjectives and Verbs ...
|
|
|
|
BASE
|
|
Show details
|
|
80 |
Investigating Cross-Linguistic Adjective Ordering Tendencies with a Latent-Variable Model ...
|
|
|
|
Abstract:
Across languages, multiple consecutive adjectives modifying a noun (e.g. "the big red dog") follow certain unmarked ordering rules. While explanatory accounts have been put forward, much of the work done in this area has relied primarily on the intuitive judgment of native speakers, rather than on corpus data. We present the first purely corpus-driven model of multi-lingual adjective ordering in the form of a latent-variable model that can accurately order adjectives across 24 different languages, even when the training and testing languages are different. We utilize this novel statistical model to provide strong converging evidence for the existence of universal, cross-linguistic, hierarchical adjective ordering tendencies. ... : 13 pages, 7 tables, 1 figure. To be published in EMNLP 2020 proceedings ...
|
|
Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
|
|
URL: https://dx.doi.org/10.48550/arxiv.2010.04755 https://arxiv.org/abs/2010.04755
|
|
BASE
|
|
Hide details
|
|
|
|