Who cites «Learning Scalar Adjective Intensity from Paraphrases»

9 papers of our library cite it, newest first: found in their bibliographies, which we read ourselves. ← the card

1. Language Models Learn Constructional Semantics, Not To Mention Syntax: Investigating LM Understanding of Paired-Focus Constructions — 2026 · Proceedings of the 30th Conference on Computational Natural Language Learning
2. Adjusting Interpretable Dimensions in Embedding Space with Human Judgments — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
3. 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)
4. A Formidable Ability: Detecting Adjectival Extremeness with DSMs — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
5. 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
6. 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)
7. Temporal Common Sense Acquisition with Minimal Supervision — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
8. How Large Are Lions? Inducing Distributions over Quantitative Attributes — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
9. ``Going on a vacation'''' takes longer than ``Going for a walk'''': A Study of Temporal Commonsense Understanding — 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)

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