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1
Challenges and Strategies in Cross-Cultural NLP ...
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2
Finding Structural Knowledge in Multimodal-BERT ...
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3
Zero-Shot Dependency Parsing with Worst-Case Aware Automated Curriculum Learning ...
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4
Parsing with Pretrained Language Models, Multiple Datasets, and Dataset Embeddings ...
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5
A Multilingual Benchmark for Probing Negation-Awareness with Minimal Pairs ...
Abstract: Negation is one of the most fundamental concepts in human cognition and language, and several natural language inference (NLI) probes have been designed to investigate pretrained language models' ability to detect and reason with negation. However, the existing probing datasets are limited to English only, and do not enable controlled probing of performance in the absence or presence of negation. In response, we present a multilingual (English, Bulgarian, German, French and Chinese) benchmark collection of NLI examples that are grammatical and correctly labeled, as a result of manual inspection and editing. We use the benchmark to probe the negation-awareness of multilingual language models and find that models that correctly predict examples with negation cues often fail to correctly predict their counter-examples without negation cues, even when the cues are irrelevant for semantic inference. ...
Keyword: Computational Linguistics; Machine Learning; Machine Learning and Data Mining; Natural Language Inference; Natural Language Processing
URL: https://underline.io/lecture/39880-a-multilingual-benchmark-for-probing-negation-awareness-with-minimal-pairs
https://dx.doi.org/10.48448/nmxw-4j45
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6
On Language Models for Creoles ...
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7
What Should/Do/Can LSTMs Learn When Parsing Auxiliary Verb Constructions? ...
NAACL 2021 2021; de Lhoneux, Miryam; Nivre, Joakim. - : Underline Science Inc., 2021
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8
I’ve got a construction looks funny – representing and recovering non-standard constructions in UD
Ruppenhofer, Josef [Verfasser]; Rehbein, Ines [Verfasser]; de Marneffe, Marie-Catherine [Herausgeber]. - Mannheim : Leibniz-Institut für Deutsche Sprache (IDS), Bibliothek, 2020
DNB Subject Category Language
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9
Køpsala: Transition-Based Graph Parsing via Efficient Training and Effective Encoding ...
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10
Comparison by Conversion: Reverse-Engineering UCCA from Syntax and Lexical Semantics ...
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11
Representation and parsing of multiword expressions: Current trends
Parmentier, Yannick; Waszczuk, Jakub; Lichte, Timm. - : Language Science Press, 2019
In: Language Science Press; (2019)
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12
Representation and parsing of multiword expressions: Current trends
Parmentier, Yannick; Waszczuk, Jakub; Lichte, Timm. - : Language Science Press, 2019
In: Language Science Press; (2019)
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13
Representation and parsing of multiword expressions: Current trends
Parmentier, Yannick; Waszczuk, Jakub; Lichte, Timm. - : Language Science Press, 2019
In: Language Science Press; (2019)
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14
Representation and parsing of multiword expressions: Current trends
Parmentier, Yannick; Waszczuk, Jakub; Lichte, Timm. - : Language Science Press, 2019
In: Language Science Press; (2019)
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15
Representation and parsing of multiword expressions: Current trends
Parmentier, Yannick; Waszczuk, Jakub; Lichte, Timm. - : Language Science Press, 2019
In: Language Science Press; (2019)
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16
Representation and parsing of multiword expressions: Current trends
Parmentier, Yannick; Waszczuk, Jakub; Lichte, Timm. - : Language Science Press, 2019
In: Language Science Press; (2019)
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17
Representation and parsing of multiword expressions: Current trends
Parmentier, Yannick; Waszczuk, Jakub; Lichte, Timm. - : Language Science Press, 2019
In: Language Science Press; (2019)
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18
Representation and parsing of multiword expressions: Current trends
Parmentier, Yannick; Waszczuk, Jakub; Lichte, Timm. - : Language Science Press, 2019
In: Language Science Press; (2019)
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19
Representation and parsing of multiword expressions: Current trends
Parmentier, Yannick; Waszczuk, Jakub; Lichte, Timm. - : Language Science Press, 2019
In: Language Science Press; (2019)
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20
Representation and parsing of multiword expressions: Current trends
Parmentier, Yannick; Waszczuk, Jakub; Lichte, Timm. - : Language Science Press, 2019
In: Language Science Press; (2019)
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