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Who cites «Are Natural Language Inference Models IMPPRESsive? Learning IMPlicature and PRESupposition»

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

  1. CEI: A Benchmark for Evaluating Pragmatic Reasoning in Language Models — 2026 · arXiv:2603.09993
  2. Can You Be More Explicit? A Task and Dataset on Explicitations of Implicit Meaning — 2026 · Proceedings of the 15th Joint Conference on Lexical and Computational Semantics (*SEM 2026)
  3. Computational models of pragmatic reasoning with flexible generation of meaning and expression alternatives — 2026 · arXiv:2607.18443
  4. DRInQ: Evaluating Conversational Implicature with Controlled Context Variation — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  5. Evaluating Communicative Belief Updates in Large Language Models via Implicature Recognition and Cancellation — 2026 · arXiv:2607.25094
  6. On Emergent Social World Models –- Evidence for Functional Integration of Theory of Mind and Pragmatic Reasoning in Language Models — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  7. POLAR: A Corpus of Questions, Responses and Argumentation in Polish Political Radio Discourse — 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference
  8. Presupposition and Reasoning in Conditionals: A Theory-Based Study of Humans and LLMs — 2026 · Proceedings of the 30th Conference on Computational Natural Language Learning
  9. There Is No Spoon: Existential Presupposition in Large Language Models — 2026 · Proceedings of the Fifteenth Language Resources and Evaluation Conference
  10. Understanding Conversational Implicatures in Humans and LLMs — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
  11. 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)
  12. Entailed Between the Lines: Incorporating Implication into NLI — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  13. For GPT-4 as with Humans: Information Structure Predicts Acceptability of Long-Distance Dependencies — 2025 · arXiv:2505.09005
  14. From Single to Multi: How LLMs Hallucinate in Multi-Document Summarization — 2025 · Findings of the Association for Computational Linguistics: NAACL 2025
  15. Let''s CONFER: A Dataset for Evaluating Natural Language Inference Models on CONditional InFERence and Presupposition — 2025 · arXiv:2506.06133
  16. Linking language model predictions to human behaviour on scalar implicatures — 2025 · Proceedings of Bridging Neurons and Symbols for Natural Language Processing and Knowledge Graphs Reasoning @ COLING 2025
  17. Meaning Beyond Truth Conditions: Evaluating Discourse Level Understanding via Anaphora Accessibility — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  18. NLI under the Microscope: What Atomic Hypothesis Decomposition Reveals — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  19. Pragmatic Theories Enhance Understanding of Implied Meanings in LLMs — 2025 · Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics
  20. Pragmatics in the Era of Large Language Models: A Survey on Datasets, Evaluation, Opportunities and Challenges — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  21. SEA-HELM: Southeast Asian Holistic Evaluation of Language Models — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  22. Understand the Implication: Learning to Think for Pragmatic Understanding — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  23. Can Your Model Tell a Negation from an Implicature? Unravelling Challenges With Intent Encoders — our card · 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  24. Do language models capture implied discourse meanings? An investigation with exhaustivity implicatures of Korean morphology — 2024 · Proceedings of the Society for Computation in Linguistics 2024
  25. Experimental Pragmatics with Machines: Testing LLM Predictions for the Inferences of Plain and Embedded Disjunctions — 2024 · arXiv:2405.05776
  26. PUB: A Pragmatics Understanding Benchmark for Assessing LLMs'' Pragmatics Capabilities — our card · 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  27. Pragmatic inference of scalar implicature by LLMs — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
  28. 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)
  29. Semantic Sensitivities and Inconsistent Predictions: Measuring the Fragility of NLI Models — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  30. (QA)$^2$: Question Answering with Questionable Assumptions — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  31. A fine-grained comparison of pragmatic language understanding in humans and language models — our card · 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  32. BHASA: A Holistic Southeast Asian Linguistic and Cultural Evaluation Suite for Large Language Models — 2023 · arXiv:2309.06085
  33. 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)
  34. DiPlomat: A Dialogue Dataset for Situated Pragmatic Reasoning — 2023 · arXiv:2306.09030
  35. Expectations over Unspoken Alternatives Predict Pragmatic Inferences — our card · 2023
  36. Fighting Bias With Bias: Promoting Model Robustness by Amplifying Dataset Biases — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  37. Imitation versus Innovation: What children can do that large language and language-and-vision models cannot (yet)? — 2023 · arXiv:2305.07666
  38. Investigating the Effect of Pre-finetuning BERT Models on NLI Involving Presuppositions — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  39. Language model acceptability judgements are not always robust to context — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  40. No Strong Feelings One Way or Another: Re-operationalizing Neutrality in Natural Language Inference — 2023 · Proceedings of the 17th Linguistic Annotation Workshop (LAW-XVII)
  41. PROPRES: Investigating the Projectivity of Presupposition with Various Triggers and Environments — 2023 · Proceedings of the 27th Conference on Computational Natural Language Learning (CoNLL)
  42. Pragmatics in Language Grounding: Phenomena, Tasks, and Modeling Approaches — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  43. We're Afraid Language Models Aren't Modeling Ambiguity — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  44. 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
  45. ANLIzing the Adversarial Natural Language Inference Dataset — 2022 · Proceedings of the Society for Computation in Linguistics 2022
  46. 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
  47. Context Matters: A Pragmatic Study of PLMs'' Negation Understanding — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  48. Investigating the Performance of Transformer-Based NLI Models on Presuppositional Inferences — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  49. Pre-trained Language Models'' Interpretation of Evaluativity Implicature: Evidence from Gradable Adjectives Usage in Context — 2022 · Proceedings of the Second Workshop on Understanding Implicit and Underspecified Language
  50. Psycholinguistic Diagnosis of Language Models' Commonsense Reasoning — 2022 · Proceedings of the First Workshop on Commonsense Representation and Reasoning (CSRR 2022)
  51. Simple but Challenging: Natural Language Inference Models Fail on Simple Sentences — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  52. TestAug: A Framework for Augmenting Capability-based NLP Tests — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  53. The Goldilocks of Pragmatic Understanding: Fine-Tuning Strategy Matters for Implicature Resolution by LLMs — 2022 · arXiv:2210.14986
  54. Diagnosing the First-Order Logical Reasoning Ability Through LogicNLI — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  55. Dimensions of Commonsense Knowledge — 2021 · arXiv:2101.04640 (Knowledge-Based Systems 2021)
  56. Dynabench: Rethinking Benchmarking in NLP — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  57. Evaluating Entity Disambiguation and the Role of Popularity in Retrieval-Based NLP — 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)
  58. Figurative Language in Recognizing Textual Entailment — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  59. GRICE: A Grammar-based Dataset for Recovering Implicature and Conversational rEasoning — our card · 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  60. He Thinks He Knows Better than the Doctors: BERT for Event Factuality Fails on Pragmatics — our card · 2021
  61. NOPE: A Corpus of Naturally-Occurring Presuppositions in English — our card · 2021 · Proceedings of the 25th Conference on Computational Natural Language Learning
  62. Predicting scalar inferences from ``or'' to ``not both'' using neural sentence encoders — our card · 2021 · Proceedings of the Society for Computation in Linguistics 2021
  63. 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
  64. Sometimes We Want Ungrammatical Translations — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
  65. UnNatural Language Inference — 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)
  66. Uncovering Constraint-Based Behavior in Neural Models via Targeted Fine-Tuning — 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)
  67. Which Linguist Invented the Lightbulb? Presupposition Verification for Question-Answering — our card · 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)
  68. ConjNLI: Natural Language Inference Over Conjunctive Sentences — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  69. Discourse structure interacts with reference but not syntax in neural language models — 2020 · Proceedings of the 24th Conference on Computational Natural Language Learning
  70. Harnessing the linguistic signal to predict scalar inferences — our card · 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  71. Mining Knowledge for Natural Language Inference from Wikipedia Categories — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  72. OCNLI: Original Chinese Natural Language Inference — 2020 · arXiv:2010.05444
  73. Temporal Reasoning in Natural Language Inference — our card · 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  74. abzianidze-2023-spacenli-evaluating-consistency-predicting-inferences
  75. alexander-2023-harnessing-il-manifesto-newspaper-archive
  76. aly-2024-tabver-tabular-fact-verification-natural
  77. dong-2026-perspectival-words-is-harder-than
  78. du-2026-it-s-not-what-you
  79. elazar-2020-extraordinary-failure-complement-coercion-crowdsourcing
  80. han-2026-crossing-cross-scale-reasoning-evaluation
  81. kim-2025-discourse-sensitivity-attraction-effects-interplay
  82. li-2025-glider-global-local-instruction-driven
  83. staliunaite-2025-dis2dis-explaining-ambiguity-fact-checking
  84. vandermeerschen-2025-supervised-unsupervised-probing-shortcut-learning
  85. zhangxiaoyi-2025-ccl25-eval-4
  86. zhu-2024-lieder-linguistically-informed-evaluation-discourse

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