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# Who cites «Right for the Wrong Reasons: Diagnosing Syntactic Heuristics in Natural Language Inference» · page 6

699 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/mccoy-2019-right-wrong-reasons-diagnosing-syntactic/)

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1. [Don''t Take the Easy Way Out: Ensemble Based Methods for Avoiding Known Dataset Biases](https://aclanthology.org/D19-1418/) *— 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)*
2. [Evaluating BERT for natural language inference: A case study on the CommitmentBank](https://aclanthology.org/D19-1630/) *— 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)*
3. [How well do NLI models capture verb veridicality?](https://md.mova.elamur.ai/free/en/docs/papers/ross-2019-how-well-do-nli-models/) *— our card · 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)*
4. [Inherent Disagreements in Human Textual Inferences](https://md.mova.elamur.ai/free/en/docs/papers/pavlick-2019-inherent-disagreements-human-textual-inferences/) *— our card · 2019*
5. [Language Models as Knowledge Bases?](https://aclanthology.org/D19-1250/) *— 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)*
6. [Probing Natural Language Inference Models through Semantic Fragments](https://arxiv.org/abs/1909.07521) *— 2019 · arXiv:1909.07521*
7. [Probing Neural Network Comprehension of Natural Language Arguments](https://aclanthology.org/P19-1459/) *— 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics*
8. [Ranking Generated Summaries by Correctness: An Interesting but Challenging Application for Natural Language Inference](https://aclanthology.org/P19-1213/) *— 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics*
9. [SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems](https://arxiv.org/abs/1905.00537) *— 2019 · arXiv:1905.00537*
10. [Towards Debiasing Fact Verification Models](https://aclanthology.org/D19-1341/) *— 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)*
11. [Universal Adversarial Triggers for Attacking and Analyzing NLP](https://aclanthology.org/D19-1221/) *— 2019 · Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP)*
12. [Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual](https://aclanthology.org/D19-6115/) *— 2019 · Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019)*
13. [When Choosing Plausible Alternatives, Clever Hans can be Clever](https://aclanthology.org/D19-6004/) *— 2019 · Proceedings of the First Workshop on Commonsense Inference in Natural Language Processing*
14. abzianidze-2023-spacenli-evaluating-consistency-predicting-inferences
15. ahia-2023-lexplain-improving-model-explanations-lexicon
16. an-2026-stad-scaffolded-task-design-identifying
17. anderson-2022-assessing-limits-distributional-hypothesis-semantic
18. antoine-2024-linguistically-motivated-evaluation-methodology-unraveling
19. aoki-2023-empirical-investigation-neural-symbolic-reasoning
20. araujo-2022-checking-hatecheck-cross-functional-analysis
21. araujo-2023-cross-functional-analysis-generalization-behavioral
22. araujo-2024-functionality-learning-through-specification-instructions
23. arunkumar-2023-real-time-visual-feedback-guide
24. asami-2024-what-makes-language-models-good
25. bailly-2020-emergence-syntax-needs-minimal-supervision
26. bailly-2023-syntax-geometry-information
27. ban-2022-testing-pre-trained-language-models
28. banerjee-2024-inffeed-influence-functions-as-feedback
29. bis-2022-paige-personalized-adaptive-interactions-graph
30. boglioni-2026-do-generalisation-results-generalise
31. bourgeade-2021-plongements-interpretables-pour-la-detection
32. braun-2024-hypothesis-driven-framework-analysis-self
33. chakraborty-2023-systematic-generalization-finetuning-analyzing-pretrained
34. chan-2024-adapting-llms-structured-natural-language
35. chauhan-2020-neu-wnut-2020-task-2
36. chen-2023-adversarial-arms-race-model-centric
37. chen-2023-making-pre-trained-language-models
38. chen-2024-what-factors-influence-llms-judgments
39. chen-2026-relevance-sufficient-evidence-detecting-evidence
40. chiang-2023-distributional-hypothesis-does-not-fully
41. chiang-2024-retrieval-augmentation-limitations-language-model
42. choudhury-2023-implications-annotation-artifacts-edge-probing
43. christopoulou-2022-training-dynamics-curriculum-learning-study
44. delaunay-2024-expliquer-une-boite-noire-sans
45. delbari-2025-beyond-accuracy-revisiting-out-distribution
46. despres-2025-accord-closing-commonsense-measurability-gap
47. dolz-2025-looking-unseen-effective-sampling-non
48. dou-2022-decorrelate-irrelevant-purify-relevant-overcome
49. downey-2023-learning-translate-learning-communicate
50. dutt-2024-investigating-generalizability-pretrained-language-models
51. elangovan-2023-effects-human-adversarial-affable-samples
52. eskin-2022-when-more-data-hurts-troubling
53. farajidizaji-2026-task-competence-instruction-following-evaluating
54. feng-2026-c2po-diagnosing-disentangling-bias-shortcuts
55. franco-2026-diagnosing-compositional-generalization-transformers-recogs
56. gabriel-2022-naturaladversaries-can-naturalistic-adversaries-be
57. gao-2025-masp-multilingual-dataset-probing-scalar
58. gao-2026-gated-tree-cross-attention-checkpoint
59. gokhale-2022-textitgeneralized-but-not-robust-comparing
60. goodale-2026-fodor-pylyshyn-s-systematicity-challenge
61. graichen-2026-grammar-transformers-systematic-review-interpretability
62. gubelmann-2025-assessing-reliability-political-bias-llms
63. guo-2023-debias-nlu-datasets-training-free
64. gupta-2024-evaluating-concurrent-robustness-language-models
65. hamdi-2026-l3irit-semeval-2026-task-4
66. han-2021-evaluation-dataset-strategy-building-robust
67. haraguchi-2023-discovering-highly-influential-shortcut-reasoning
68. he-2024-mitigating-shortcuts-language-models-soft
69. he-2025-layer-wise-minimal-pair-probing
70. heredia-2024-xnlieu-dataset-cross-lingual-nli
71. hojer-2025-research-community-perspectives-intelligence-large
72. honda-2025-exploring-explanations-improves-robustness-context
73. howard-2022-neurocounterfactuals-beyond-minimal-edit-counterfactuals
74. hu-2024-reduce-redundancy-then-rerank-enhancing
75. huang-2023-statistically-profiling-biases-natural-language
76. igbaria-2024-learning-others-similarity-based-regularization
77. ingimundarson-2026-who-benchmarks-benchmarks-case-study
78. jafaritazehjani-2019-visually-grounded-generation-entailments-premises
79. jiang-2026-immediate-inference-missing-foundation-large
80. jie-2025-llms-struggle-nli-perfect-aspect
81. joishy-2025-flying-pigs-far-evaluating-llm
82. jolly-2020-can-pre-training-help-vqa
83. jullien-2026-compartmentalised-agentic-reasoning-clinical-nli
84. junias-2026-logical-commonsenseqa-benchmark-logical-commonsense
85. k-2026-continual-learning-modelling-low-resource
86. kamoi-2026-efficient-prm-training-data-synthesis
87. kannangara-2026-student-llms-inherit-ood-robustness
88. karakas-2026-lemmas-dependencies-what-signals-drive
89. karakas-2026-plausibility-as-commonsense-reasoning-humans
90. kavumba-2021-learning-learn-be-right-right
91. kim-2023-roast-robustifying-language-models-adversarial
92. kim-2025-benchmark-profiling-mechanistic-diagnosis-llm
93. kogkalidis-2024-oyxoy-modern-nlp-test-suite
94. korakakis-2025-mitigating-shortcut-learning-interpolated-learning
95. kumon-2026-fine-grained-analysis-shared-syntactic
96. kuribayashi-2025-does-vision-accelerate-hierarchical-generalization
97. larraya-2026-assessing-logical-coherence-llms-fine
98. larson-2023-evaluation-document-classification-rvl-cdip
99. lasri-2023-econberta-robust-extraction-named-entities
100. lee-2023-autotrigger-label-efficient-robust-named

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