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

1. Transformers Learning Contrafactives: The Importance of Data Distributions — 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 — 2025 · arXiv:2506.06133
3. Exploring Continual Learning of Compositional Generalization in NLI — 2024 · Transactions of the Association for Computational Linguistics
4. (QA)$^2$: Question Answering with Questionable Assumptions — 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 — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
6. Finding Common Ground: Annotating and Predicting Common Ground in Spoken Conversations — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
7. PROPRES: Investigating the Projectivity of Presupposition with Various Triggers and Environments — 2023 · Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL)
8. Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
9. SETI: Systematicity Evaluation of Textual Inference — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
10. Towards Generative Event Factuality Prediction — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
11. BeSt: The Belief and Sentiment Corpus — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
12. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models — 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 — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
14. Re-Examining FactBank: Predicting the Author''s Presentation of Factuality — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
15. Exploring Transitivity in Neural NLI Models through Veridicality — 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 — 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 — our card · 2021
18. Monotonicity Marking from Universal Dependency Trees — 2021 · Proceedings of the 14th International Conference on Computational Semantics (IWCS)
19. NOPE: A Corpus of Naturally-Occurring Presuppositions in English — our card · 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning
20. Robustness Gym: Unifying the NLP Evaluation Landscape — 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 — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
22. Detecting Stance in Media On Global Warming — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
23. Do Neural Models Learn Systematicity of Monotonicity Inference in Natural Language? — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
24. Temporal Reasoning in 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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