Mova0.5 pre-release⌕
☰
home / docs / papers / cited-by / Who cites «Was It Good? It Was Provocative.'' Learning the Meaning of Scalar Adjectives»

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

  1. On the Dangers of Naïve Replication: The Case of Implicature — 2025 · Proceedings of the Society for Computation in Linguistics 2025
  2. Probing Large Language Models for Scalar Adjective Lexical Semantics and Scalar Diversity Pragmatics — 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 — 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 — our card · 2023
  5. Disentangling Indirect Answers to Yes-No Questions in Real Conversations — 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 — our card · 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  7. Representing Numbers in NLP: a Survey and a Vision — 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 — 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 — 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 — 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 — 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 — 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 — 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 — 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 — 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 — 2015 · Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing
  17. Corpus-based discovery of semantic intensity scales — 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 — 2015 · Proceedings of the International Conference Recent Advances in Natural Language Processing
  19. Deriving Adjectival Scales from Continuous Space Word Representations — 2013 · Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing
  20. Good, Great, Excellent: Global Inference of Semantic Intensities — 2013
  21. Compositional Matrix-Space Models for Sentiment Analysis — 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

This page in Markdown → https://md.mova.elamur.ai/free/en/docs/papers/cited-by/marneffe-2010-was-it-good-it-was/