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Is "my favorite new movie" my favorite movie? Probing the Understanding of Recursive Noun Phrases ...
Lyu, Qing; Zheng, Hua; Li, Daoxin. - : arXiv, 2021
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Scalar Adjective Identification and Multilingual Ranking ...
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Scalar Adjective Identification and Multilingual Ranking ...
NAACL 2021 2021; Apidianaki, Marianna; Garí Soler, Aina. - : Underline Science Inc., 2021
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4
Let's Play Mono-Poly: BERT Can Reveal Words' Polysemy Level and Partitionability into Senses ...
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Let's Play mono-poly: BERT Can Reveal Words' Degree of Polysemy ...
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6
ALL Dolphins Are Intelligent and SOME Are Friendly: Probing BERT for Nouns' Semantic Properties and their Prototypicality ...
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7
BERT Knows Punta Cana is not just beautiful, it's gorgeous: Ranking Scalar Adjectives with Contextualised Representations ...
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8
MULTISEM at SemEval-2020 Task 3: Fine-tuning BERT for Lexical Meaning ...
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9
Common sense or world knowledge? Investigating adapter-based knowledge injection into pretrained transformers
Lauscher, Anne; Majewska, Olga; Ribeiro, Leonardo F. R.. - : Association for Computational Linguistics, 2020
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10
Knowledge graphs meet moral values
Hulpus, Ioana; Kobbe, Jonathan; Stuckenschmidt, Heiner. - : Association for Computational Linguistics, 2020
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11
SumQE: a BERT-based Summary Quality Estimation Model ...
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12
Complexity-Weighted Loss and Diverse Reranking for Sentence Simplification ...
Abstract: Sentence simplification is the task of rewriting texts so they are easier to understand. Recent research has applied sequence-to-sequence (Seq2Seq) models to this task, focusing largely on training-time improvements via reinforcement learning and memory augmentation. One of the main problems with applying generic Seq2Seq models for simplification is that these models tend to copy directly from the original sentence, resulting in outputs that are relatively long and complex. We aim to alleviate this issue through the use of two main techniques. First, we incorporate content word complexities, as predicted with a leveled word complexity model, into our loss function during training. Second, we generate a large set of diverse candidate simplifications at test time, and rerank these to promote fluency, adequacy, and simplicity. Here, we measure simplicity through a novel sentence complexity model. These extensions allow our models to perform competitively with state-of-the-art systems while generating simpler ... : 11 pages, North American Association of Computational Linguistics (NAACL 2019) ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://dx.doi.org/10.48550/arxiv.1904.02767
https://arxiv.org/abs/1904.02767
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13
Word Usage Similarity Estimation with Sentence Representations and Automatic Substitutes ...
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14
Simplification Using Paraphrases and Context-Based Lexical Substitution
In: Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies ; https://hal.archives-ouvertes.fr/hal-01838519 ; Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Association for Computational Linguistics, Jun 2018, Nouvelle Orléans, United States (2018)
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15
Automated Paraphrase Lattice Creation for HyTER Machine Translation Evaluation
In: Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies ; https://hal.archives-ouvertes.fr/hal-01838521 ; Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Association for Computational Linguistics Jun 2018, Nouvelle Orléans, United States (2018)
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16
Comparing Constraints for Taxonomic Organization
In: Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies ; https://hal.archives-ouvertes.fr/hal-01838520 ; Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Association for Computational Linguistics Jun 2018, Nouvelle Orléans, United States (2018)
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17
UniMa at SemEval-2018 Task 7 : semantic relation extraction and classification from scientific publications
Ponzetto, Simone Paolo; Zhang, Jingyi; Keiper, Thorsten. - : Association for Computational Linguistics, 2018
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18
Mapping the Paraphrase Database to WordNet
In: Conference on Lexical and Computational Semantics ; https://hal.archives-ouvertes.fr/hal-01838527 ; Conference on Lexical and Computational Semantics, Aug 2017, Vancouver, Canada (2017)
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19
Learning Antonyms with Paraphrases and a Morphology-aware Neural Network
In: Conference on Lexical and Computational Semantics ; https://hal.archives-ouvertes.fr/hal-01838526 ; Conference on Lexical and Computational Semantics, Aug 2017, Vancouver, Canada (2017)
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20
Word Sense Filtering Improves Embedding-Based Lexical Substitution
In: Conference of the European Chapter of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-01838524 ; Conference of the European Chapter of the Association for Computational Linguistics , Apr 2017, Valencia, Spain (2017)
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