[Mova](https://md.mova.elamur.ai/free/en/) · [this page in HTML](https://mova.elamur.ai/free/en/docs/papers/cited-by/degen-2015-investigating-distribution-some-but-not/)

[home](https://md.mova.elamur.ai/free/en/) / [docs](https://md.mova.elamur.ai/free/en/docs/) / [papers](https://md.mova.elamur.ai/free/en/docs/papers/) / [cited-by](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/) / Who cites «Investigating the distribution of some (but not all) implicatures using corpora and web-based methods»

# Who cites «Investigating the distribution of some (but not all) implicatures using corpora and web-based methods»

14 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/degen-2015-investigating-distribution-some-but-not/)

1. [Evaluating Communicative Belief Updates in Large Language Models via Implicature Recognition and Cancellation](https://arxiv.org/abs/2607.25094) *— 2026 · arXiv:2607.25094*
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. [SIGA: A Naturalistic NLI Dataset of English Scalar Implicatures with Gradable Adjectives](https://md.mova.elamur.ai/free/en/docs/papers/nizamani-2024-siga-naturalistic-nli-dataset-english/) *— our card · 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)*
4. [Complementizers on edge: On the boundaries between syntax and pragmatics in Ibero-Romance (Language Science Press, Open Romance Linguistics, 2022)](https://zenodo.org/records/6907848) *— 2022 · monograph*
5. [Investigating the Performance of Transformer-Based NLI Models on Presuppositional Inferences](https://aclanthology.org/2022.coling-1.65/) *— 2022 · Proceedings of the 29th International Conference on Computational Linguistics*
6. [Pragmatic and Logical Inferences in NLI Systems: The Case of Conjunction Buttressing](https://md.mova.elamur.ai/free/en/docs/papers/pedinotti-2022-pragmatic-logical-inferences-nli-systems/) *— our card · 2022 · Proceedings of the Second Workshop on Understanding Implicit and Underspecified Language*
7. [Predicting scalar diversity with context-driven uncertainty over alternatives](https://aclanthology.org/2022.cmcl-1.8/) *— 2022 · Proceedings of the Workshop on Cognitive Modeling and Computational Linguistics*
8. [Predicting scalar inferences from ``or'' to ``not both'' using neural sentence encoders](https://md.mova.elamur.ai/free/en/docs/papers/li-2021-predicting-scalar-inferences-or-not/) *— our card · 2021 · Proceedings of the Society for Computation in Linguistics 2021*
9. [Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESupposition](https://md.mova.elamur.ai/free/en/docs/papers/jeretic-2020-are-natural-language-inference-models/) *— our card · 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
10. [Harnessing the linguistic signal to predict scalar inferences](https://md.mova.elamur.ai/free/en/docs/papers/schuster-2020-harnessing-linguistic-signal-predict-scalar/) *— our card · 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
11. [Conversational implicatures in English dialogue: Annotated dataset](https://md.mova.elamur.ai/free/en/docs/papers/george-2019-conversational-implicatures-english-dialogue-annotated/) *— our card · 2019 · arXiv:1911.10704*
12. [SQUINKY! A Corpus of Sentence-level Formality, Informativeness, and Implicature](https://arxiv.org/abs/1506.02306) *— 2015 · arXiv:1506.02306*
13. azin-2026-do-language-models-know-theo
14. han-2026-crossing-cross-scale-reasoning-evaluation
- [← previous Who cites «On Coreferring: Coreference in MUC and Related Annotation Schemes»](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/deemter-2000-coreferring-coreference-muc-related-annotation/)
- [next → Who cites «Synthetic Data for English Lexical Normalization: How Close Can We Get to Manually Annotated Data?»](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/dekker-2020-synthetic-data-english-lexical-normalization/)
- [↑ back to papers/cited-by/](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/)