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# Who cites «Was It Good? It Was Provocative.'' Learning the Meaning of Scalar Adjectives»

25 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. [← the card](https://md.mova.elamur.ai/free/en/docs/papers/marneffe-2010-was-it-good-it-was/)

1. [On the Dangers of Naïve Replication: The Case of Implicature](https://aclanthology.org/2025.scil-1.17/) *— 2025 · Proceedings of the Society for Computation in Linguistics 2025*
2. [Probing Large Language Models for Scalar Adjective Lexical Semantics and Scalar Diversity Pragmatics](https://aclanthology.org/2024.lrec-main.1141/) *— 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
3. [SIGA: A Naturalistic NLI Dataset of English Scalar Implicatures with Gradable Adjectives](https://md.mova.elamur.ai/free/en/docs/papers/nizamani-2024-siga-naturalistic-nli-dataset-english/) *— our card · 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
4. [Expectations over Unspoken Alternatives Predict Pragmatic Inferences](https://md.mova.elamur.ai/free/en/docs/papers/hu-2023-expectations-over-unspoken-alternatives-predict/) *— our card · 2023*
5. [Disentangling Indirect Answers to Yes-No Questions in Real Conversations](https://md.mova.elamur.ai/free/en/docs/papers/sanagavarapu-2022-disentangling-indirect-answers-yes-no/) *— our card · 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
6. [GRICE: A Grammar-based Dataset for Recovering Implicature and Conversational rEasoning](https://md.mova.elamur.ai/free/en/docs/papers/zheng-2021-grice-grammar-based-dataset-recovering/) *— our card · 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
7. [Representing Numbers in NLP: a Survey and a Vision](https://aclanthology.org/2021.naacl-main.53/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
8. [Scalar Adjective Identification and Multilingual Ranking](https://aclanthology.org/2021.naacl-main.370/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
9. [BERT Knows Punta Cana is not just beautiful, it''s gorgeous: Ranking Scalar Adjectives with Contextualised Representations](https://aclanthology.org/2020.emnlp-main.598/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
10. [``I''d rather just go to bed'''': Understanding Indirect Answers](https://md.mova.elamur.ai/free/en/docs/papers/louis-2020-i-d-rather-just-go/) *— our card · 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
11. [Is the Red Square Big? MALeViC: Modeling Adjectives Leveraging Visual Contexts](https://aclanthology.org/D19-1285/) *— 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)*
12. [Learning Scalar Adjective Intensity from Paraphrases](https://md.mova.elamur.ai/free/en/docs/papers/cocos-2018-learning-scalar-adjective-intensity-paraphrases/) *— our card · 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing*
13. [Numeracy for Language Models: Evaluating and Improving their Ability to Predict Numbers](https://aclanthology.org/P18-1196/) *— 2018 · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
14. [Identification, characterization, and grounding of gradable terms in clinical text](https://aclanthology.org/W16-2903/) *— 2016 · Proceedings of the 15th Workshop on Biomedical Natural Language Processing*
15. [The Instantiation Discourse Relation: A Corpus Analysis of Its Properties and Improved Detection](https://aclanthology.org/N16-1141/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
16. [A Vector Space Approach for Aspect Based Sentiment Analysis](https://aclanthology.org/W15-1516/) *— 2015 · Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing*
17. [Corpus-based discovery of semantic intensity scales](https://aclanthology.org/N15-1051/) *— 2015 · Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
18. [Ordering adverbs by their scaling effect on adjective intensity](https://aclanthology.org/R15-1071/) *— 2015 · Proceedings of the International Conference Recent Advances in Natural Language Processing*
19. [Deriving Adjectival Scales from Continuous Space Word Representations](https://aclanthology.org/D13-1169/) *— 2013 · Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing*
20. [Good, Great, Excellent: Global Inference of Semantic Intensities](https://aclanthology.org/Q13-1023/) *— 2013*
21. [Compositional Matrix-Space Models for Sentiment Analysis](https://aclanthology.org/D11-1016/) *— 2011 · Proceedings of the 2011 Conference on Empirical Methods in Natural Language Processing*
22. flekova-2015-analysing-domain-suitability-sentiment-lexicon
23. tran-2014-extracting-latent-attributes-video-scenes
24. wang-2024-interpreting-answers-yes-no-questions
25. wilkinson-2015-initial-steps-building-lexicon-adjectives
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