Who cites «Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering»

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

1. Contextualizing Toxicity: An Annotation Framework for Unveiling Pragmatics in Conversations of Online Discussion Forums — 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference
2. Don''t `Well, Actually'' Me Unless You Know What You''re Talking About: Weak Presupposition Verification Degrades General QA Performance — 2026 · arXiv:2608.06539
3. Thesis Proposal: Intentional Inference for Insight Generation — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
4. Can LLMs Ground when they (Don''t) Know: A Study on Direct and Loaded Political Questions — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
5. Don''t Let It Hallucinate: Premise Verification via Retrieval-Augmented Logical Reasoning — 2025 · arXiv:2504.06438
6. If We May De-Presuppose: Robustly Verifying Claims through Presupposition-Free Question Decomposition — 2025 · Proceedings of the 14th Joint Conference on Lexical and Computational Semantics (*SEM 2025)
7. Measuring Chain of Thought Faithfulness by Unlearning Reasoning Steps — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
8. NeoQA: Evidence-based Question Answering with Generated News Events — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
9. No Questions are Stupid, but some are Poorly Posed: Understanding Poorly-Posed Information-Seeking Questions — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
10. Asking More Informative Questions for Grounded Retrieval — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
11. Enhancing Large Language Models Against Inductive Instructions with Dual-critique Prompting — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
12. I Could''ve Asked That: Reformulating Unanswerable Questions — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
13. LIEDER: Linguistically-Informed Evaluation for Discourse Entity Recognition — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
14. PUB: A Pragmatics Understanding Benchmark for Assessing LLMs'' Pragmatics Capabilities — our card · 2024 · Findings of the Association for Computational Linguistics: ACL 2024
15. Pregnant Questions: The Importance of Pragmatic Awareness in Maternal Health Question Answering — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
16. Who Did You Blame When Your Project Failed? Designing a Corpus for Presupposition Generation in Cross-Examination Dialogues — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
17. (QA)$^2$: Question Answering with Questionable Assumptions — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
18. Answering Unanswered Questions through Semantic Reformulations in Spoken QA — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 5: Industry Track)
19. Bullshit, Pragmatic Deception, and Natural Language Processing — 2023
20. CREPE: Open-Domain Question Answering with False Presuppositions — our card · 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
21. DisentQA: Disentangling Parametric and Contextual Knowledge with Counterfactual Question Answering — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
22. EpiK-Eval: Evaluation for Language Models as Epistemic Models — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
23. How Language Model Hallucinations Can Snowball — 2023 · arXiv:2305.13534
24. How Well Do Large Language Models Perform on Faux Pas Tests? — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
25. Large Language Model Programs — 2023 · arXiv:2305.05364
26. PreWoMe: Exploiting Presuppositions as Working Memory for Long Form Question Answering — our card · 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
27. SCENE: Self-Labeled Counterfactuals for Extrapolating to Negative Examples — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
28. Selective-LAMA: Selective Prediction for Confidence-Aware Evaluation of Language Models — 2023 · Findings of the Association for Computational Linguistics: EACL 2023
29. When Your Language Model Cannot Even Do Determiners Right: Probing for Anti-Presuppositions and the Maximize Presupposition! Principle — our card · 2023 · Proceedings of the 6th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP
30. Won''t Get Fooled Again: Answering Questions with False Premises — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
31. FaVIQ: FAct Verification from Information-seeking Questions — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
32. Few-Shot Self-Rationalization with Natural Language Prompts — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
33. How Do We Answer Complex Questions: Discourse Structure of Long-form Answers — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
34. The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs — 2022 · arXiv:2210.14986
35. Can NLI Models Verify QA Systems' Predictions? — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
36. Challenges in Information-Seeking QA: Unanswerable Questions and Paragraph Retrieval — 2021 · Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
37. SituatedQA: Incorporating Extra-Linguistic Contexts into QA — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing