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# Who cites «How well do NLI models capture verb veridicality?»

31 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/ross-2019-how-well-do-nli-models/)

1. [Transformers Learning Contrafactives: The Importance of Data Distributions](https://aclanthology.org/2026.brigap-1.10/) *— 2026 · Proceedings of the Third Workshop on the Bridges and Gaps between Formal and Computational Linguistics (BriGap-3)*
2. [Let''s CONFER: A Dataset for Evaluating Natural Language Inference Models on CONditional InFERence and Presupposition](https://arxiv.org/abs/2506.06133) *— 2025 · arXiv:2506.06133*
3. [Exploring Continual Learning of Compositional Generalization in NLI](https://aclanthology.org/2024.tacl-1.51/) *— 2024 · Transactions of the Association for Computational Linguistics*
4. [(QA)$^2$: Question Answering with Questionable Assumptions](https://aclanthology.org/2023.acl-long.472/) *— 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
5. [Are Language Models Worse than Humans at Following Prompts? It's Complicated](https://aclanthology.org/2023.findings-emnlp.514/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
6. [Finding Common Ground: Annotating and Predicting Common Ground in Spoken Conversations](https://aclanthology.org/2023.findings-emnlp.551/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
7. [PROPRES: Investigating the Projectivity of Presupposition with Various Triggers and Environments](https://aclanthology.org/2023.conll-1.9/) *— 2023 · Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL)*
8. [Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches](https://aclanthology.org/2023.findings-emnlp.840/) *— 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023*
9. [SETI: Systematicity Evaluation of Textual Inference](https://aclanthology.org/2023.findings-acl.252/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
10. [Towards Generative Event Factuality Prediction](https://aclanthology.org/2023.findings-acl.44/) *— 2023 · Findings of the Association for Computational Linguistics: ACL 2023*
11. [BeSt: The Belief and Sentiment Corpus](https://aclanthology.org/2022.lrec-1.262/) *— 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference*
12. [Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models](https://arxiv.org/abs/2206.04615) *— 2022 · arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj*
13. [Human Guided Exploitation of Interpretable Attention Patterns in Summarization and Topic Segmentation](https://aclanthology.org/2022.emnlp-main.694/) *— 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing*
14. [Re-Examining FactBank: Predicting the Author''s Presentation of Factuality](https://aclanthology.org/2022.coling-1.66/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
15. [Exploring Transitivity in Neural NLI Models through Veridicality](https://aclanthology.org/2021.eacl-main.78/) *— 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume*
16. [Figurative Language in Recognizing Textual Entailment](https://aclanthology.org/2021.findings-acl.297/) *— 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021*
17. [He Thinks He Knows Better than the Doctors: BERT for Event Factuality Fails on Pragmatics](https://md.mova.elamur.ai/free/en/docs/papers/jiang-2021-he-thinks-he-knows-better/) *— our card · 2021*
18. [Monotonicity Marking from Universal Dependency Trees](https://aclanthology.org/2021.iwcs-1.12/) *— 2021 · Proceedings of the 14th International Conference on Computational Semantics (IWCS)*
19. [NOPE: A Corpus of Naturally-Occurring Presuppositions in English](https://md.mova.elamur.ai/free/en/docs/papers/parrish-2021-nope-corpus-naturally-occurring-presuppositions/) *— our card · 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning*
20. [Robustness Gym: Unifying the NLP Evaluation Landscape](https://aclanthology.org/2021.naacl-demos.6/) *— 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Demonstrations*
21. [ConjNLI: Natural Language Inference Over Conjunctive Sentences](https://aclanthology.org/2020.emnlp-main.661/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
22. [Detecting Stance in Media On Global Warming](https://aclanthology.org/2020.findings-emnlp.296/) *— 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020*
23. [Do Neural Models Learn Systematicity of Monotonicity Inference in Natural Language?](https://aclanthology.org/2020.acl-main.543/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
24. [Temporal Reasoning in Natural Language Inference](https://md.mova.elamur.ai/free/en/docs/papers/vashishtha-2020-temporal-reasoning-natural-language-inference/) *— our card · 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020*
25. azin-2026-do-language-models-know-theo
26. cong-2025-overview-ccl25-eval-task-4
27. elazar-2020-extraordinary-failure-complement-coercion-crowdsourcing
28. kozachenko-2025-role-linguistic-features-llm-performance
29. li-2025-glider-global-local-instruction-driven
30. murzaku-2025-zero-shot-belief-hard-problem
31. soeder-2023-crowdsourcing-veridicality-annotations-spanish-can
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