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| 121 |
Analysis of Language Change in Collaborative Instruction Following
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In: Proceedings of the Society for Computation in Linguistics (2022)
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| 122 |
SCiL 2022 Editors' Note
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In: Proceedings of the Society for Computation in Linguistics (2022)
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| 123 |
TopiOCQA: Open-domain Conversational Question Answering with Topic Switching
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In: Transactions of the Association for Computational Linguistics, Vol 10, Pp 468-483 (2022) (2022)
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| 124 |
PADA: Example-based Prompt Learning for on-the-fly Adaptation to Unseen Domains
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In: Transactions of the Association for Computational Linguistics, Vol 10, Pp 414-433 (2022) (2022)
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| 125 |
VILA: Improving Structured Content Extraction from Scientific PDFs Using Visual Layout Groups
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In: Transactions of the Association for Computational Linguistics, Vol 10, Pp 376-392 (2022) (2022)
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| 126 |
LOT: A Story-Centric Benchmark for Evaluating Chinese Long Text Understanding and Generation
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In: Transactions of the Association for Computational Linguistics, Vol 10, Pp 434-451 (2022) (2022)
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| 127 |
Data-driven Model Generalizability in Crosslinguistic Low-resource Morphological Segmentation
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In: Transactions of the Association for Computational Linguistics, Vol 10, Pp 393-413 (2022) (2022)
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Abstract:
AbstractCommon designs of model evaluation typically focus on monolingual settings, where different models are compared according to their performance on a single data set that is assumed to be representative of all possible data for the task at hand. While this may be reasonable for a large data set, this assumption is difficult to maintain in low-resource scenarios, where artifacts of the data collection can yield data sets that are outliers, potentially making conclusions about model performance coincidental. To address these concerns, we investigate model generalizability in crosslinguistic low-resource scenarios. Using morphological segmentation as the test case, we compare three broad classes of models with different parameterizations, taking data from 11 languages across 6 language families. In each experimental setting, we evaluate all models on a first data set, then examine their performance consistency when introducing new randomly sampled data sets with the same size and when applying the trained models to unseen test sets of varying sizes. The results demonstrate that the extent of model generalization depends on the characteristics of the data set, and does not necessarily rely heavily on the data set size. Among the characteristics that we studied, the ratio of morpheme overlap and that of the average number of morphemes per word between the training and test sets are the two most prominent factors. Our findings suggest that future work should adopt random sampling to construct data sets with different sizes in order to make more responsible claims about model evaluation.
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Keyword:
Computational linguistics. Natural language processing; P98-98.5
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URL: https://doaj.org/article/45db27c964df45bdb6712eadb016a91a
https://doi.org/10.1162/tacl_a_00467
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| 128 |
Time-Aware Language Models as Temporal Knowledge Bases
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In: Transactions of the Association for Computational Linguistics, Vol 10, Pp 257-273 (2022) (2022)
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| 129 |
Neuro-symbolic Natural Logic with Introspective Revision for Natural Language Inference
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In: Transactions of the Association for Computational Linguistics, Vol 10, Pp 240-256 (2022) (2022)
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| 130 |
Phylogenetic trees: Grammar versus vocabulary
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In: Russian Journal of Linguistics, Vol 26, Iss 1, Pp 31-50 (2022) (2022)
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| 131 |
Les débuts de la phraséologie et les premières « phraséologies historiques » italo-françaises
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In: Linguistik Online, Vol 113, Iss 1 (2022) (2022)
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| 132 |
Formen und Funktionen des Konjunktivs II in historischen ostoberdeutschen Predigten.
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In: Linguistik Online, Vol 114, Iss 2 (2022) (2022)
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| 133 |
Zur Sprachdynamik des Konjunktivs im Bairischen in Österreich
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In: Linguistik Online, Vol 114, Iss 2 (2022) (2022)
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| 134 |
Die Konjunktiv-II-Bildung im Kontext von Partikelverben in den Basisdialekten Salzburgs
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In: Linguistik Online, Vol 114, Iss 2 (2022) (2022)
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| 135 |
Evaluating Explanations: How Much Do Explanations from the Teacher Aid Students?
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In: Transactions of the Association for Computational Linguistics, Vol 10, Pp 359-375 (2022) (2022)
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| 136 |
Informationen zu den Beitragenden/Information about the authors
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In: Linguistik Online, Vol 113, Iss 1 (2022) (2022)
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| 137 |
A Coordenação na Gramática Discursivo-Funcional
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In: Linguistik Online, Vol 113, Iss 1 (2022) (2022)
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| 138 |
Der Konjunktiv II in den ruralen Basisdialekten Österreichs.
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In: Linguistik Online, Vol 114, Iss 2 (2022) (2022)
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| 139 |
Konjunktiv II-Variation im urbanen Sprachgebrauch in Österreich
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In: Linguistik Online, Vol 114, Iss 2 (2022) (2022)
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| 140 |
Der Konjunktiv II in Salzburger Varietäten: Grammatik, Gebrauch, soziale Faktoren
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In: Linguistik Online, Vol 114, Iss 2 (2022) (2022)
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