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# Who cites «A Corpus for Reasoning About Natural Language Grounded in Photographs (NLVR2)» · page 2

192 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/suhr-2019-corpus-reasoning-natural-language-grounded/)

Pages: [1](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/suhr-2019-corpus-reasoning-natural-language-grounded/) · **2**

1. [Evaluating Models' Local Decision Boundaries via Contrast Sets](https://md.mova.elamur.ai/free/en/docs/papers/gardner-2020-evaluating-models-local-decision-boundaries/) *— our card · 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020*
2. [Experience Grounds Language](https://aclanthology.org/2020.emnlp-main.703/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
3. [How Can We Accelerate Progress Towards Human-like Linguistic Generalization?](https://aclanthology.org/2020.acl-main.465/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
4. [Learning to Represent Image and Text with Denotation Graph](https://aclanthology.org/2020.emnlp-main.60/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
5. [MUTANT: A Training Paradigm for Out-of-Distribution Generalization in Visual Question Answering](https://aclanthology.org/2020.emnlp-main.63/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
6. [New Protocols and Negative Results for Textual Entailment Data Collection](https://aclanthology.org/2020.emnlp-main.658/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
7. [Obtaining Faithful Interpretations from Compositional Neural Networks](https://aclanthology.org/2020.acl-main.495/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
8. [Oscar: Object-Semantics Aligned Pre-training for Vision-Language Tasks](https://arxiv.org/abs/2004.06165) *— 2020 · arXiv:2004.06165*
9. [Profile Consistency Identification for Open-domain Dialogue Agents](https://aclanthology.org/2020.emnlp-main.539/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
10. [Representation, Learning and Reasoning on Spatial Language for Downstream NLP Tasks](https://aclanthology.org/2020.emnlp-tutorials.5/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Tutorial Abstracts*
11. [The Hateful Memes Challenge: Detecting Hate Speech in Multimodal Memes](https://arxiv.org/abs/2005.04790) *— 2020 · arXiv:2005.04790*
12. [Understanding tables with intermediate pre-training](https://aclanthology.org/2020.findings-emnlp.27/) *— 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020*
13. [VD-BERT: A Unified Vision and Dialog Transformer with BERT](https://aclanthology.org/2020.emnlp-main.269/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
14. [What Does BERT with Vision Look At?](https://aclanthology.org/2020.acl-main.469/) *— 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics*
15. [X-LXMERT: Paint, Caption and Answer Questions with Multi-Modal Transformers](https://aclanthology.org/2020.emnlp-main.707/) *— 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
16. [多模态视觉语言表征学习研究综述](https://jos.org.cn/jos/article/abstract/6125) *— 2020 · 软件学报 (Journal of Software)*
17. [Are We Modeling the Task or the Annotator? An Investigation of Annotator Bias in Natural Language Understanding Datasets](https://aclanthology.org/D19-1107/) *— 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)*
18. [Expressing Visual Relationships via Language](https://aclanthology.org/P19-1182/) *— 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics*
19. [GQA: A New Dataset for Real-World Visual Reasoning and Compositional Question Answering](https://arxiv.org/abs/1902.09506) *— 2019 · arXiv:1902.09506*
20. [Is the Red Square Big? MALeViC: Modeling Adjectives Leveraging Visual Contexts](https://aclanthology.org/D19-1285/) *— 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)*
21. [LXMERT: Learning Cross-Modality Encoder Representations from Transformers](https://aclanthology.org/D19-1514/) *— 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)*
22. [Neural Naturalist: Generating Fine-Grained Image Comparisons](https://aclanthology.org/D19-1065/) *— 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)*
23. [TabFact: A Large-scale Dataset for Table-based Fact Verification](https://arxiv.org/abs/1909.02164) *— 2019 · arXiv:1909.02164*
24. [UNITER: UNiversal Image-TExt Representation Learning](https://arxiv.org/abs/1909.11740) *— 2019 · arXiv:1909.11740*
25. [VisualBERT: A Simple and Performant Baseline for Vision and Language](https://arxiv.org/abs/1908.03557) *— 2019 · arXiv:1908.03557*
26. [Touchdown: Natural Language Navigation and Spatial Reasoning in Visual Street Environments](https://arxiv.org/abs/1811.12354) *— 2018 · arXiv:1811.12354 · Published in CVPR 2019*
27. akula-2021-mind-context-impact-contextualization-neural
28. anugraha-2025-m4-rag-massive-scale-multilingual
29. attwell-2024-attribute-diversity-determines-systematicity-gap
30. banerjee-2026-mischief-benchmark-minimal-pairs-safety
31. bexte-2024-evil-probe-composite-benchmark-extensive
32. bugliarello-2023-weakly-supervised-learning-visual-relations
33. byun-2024-efficient-post-hoc-framework-reducing
34. cafagna-2022-understanding-cross-modal-interactions-v
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40. chow-2023-travlr-now-you-see-it
41. das-2026-more-images-more-problems-controlled
42. dhor-2026-itnet-learnable-integral-transform-that
43. gao-2025-do-vision-language-models-have
44. garcia-2023-processing-referential-ambiguities-situated-dialogue
45. guhan-2024-tame-rd-text-assisted-replication
46. hahn-2022-transformer-based-localization-embodied-dialog
47. hakimov-2023-images-language-space-exploring-suitability
48. hu-2023-meta-learning-vision-language-cross
49. iokawa-2024-visual-textual-entailment-quantities-model
50. jiang-2023-vision-language-pre-training-contrastive
51. kim-2024-sparseflow-accelerating-transformers-sparsifying-information
52. kim-2026-localizing-events-space-comparing-humans
53. kordjamshidi-2024-spatial-temporal-language-understanding-representation
54. kundu-2025-looking-beyond-pixels-evaluating-visual
55. lee-2025-tamp-token-adaptive-layerwise-pruning
56. li-2024-frog-evaluating-fuzzy-reasoning-generalized
57. lin-2020-adjusting-image-attributes-localized-regions
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59. liu-2024-finecops-ref-new-dataset-task
60. liu-2024-mibench-evaluating-multimodal-large-language
61. manea-2025-multilingual-vision-language-models-survey
62. martin-2026-clevr-3d-deref
63. parfenova-2021-probing-cross-modal-representations-multi
64. patil-2023-debiasing-multimodal-models-causal-information
65. pikabea-2025-breaking-language-barriers-visual-language
66. ravishankara-2025-artificial-intelligence-cognitive-examination-survey
67. reinhardt-2024-improving-vision-language-cross-lingual
68. ren-2022-leaner-faster-two-stage-model
69. ruan-2021-sattiy-semeval-2021-task-9
70. salin-2023-etat-des-lieux-des-transformers
71. samin-2025-colorfoil-investigating-color-blindness-large
72. shin-2021-transformer-exclusive-cross-modal-representation
73. sun-2023-fusion-or-defusion-flexible-vision
74. sun-2024-lightvlp-lightweight-vision-language-pre
75. suzuki-2021-building-video-language-dataset-human
76. tater-2025-absvis-benchmarking-how-humans-vision
77. tou-2024-curriculum-masking-vision-language-pretraining
78. vickers-2021-factuality-efficient-integration-relevant-facts
79. wang-2022-anchor-based-relative-position-embedding
80. wang-2023-accelerating-vision-language-pretraining-free
81. wang-2023-dataset-bias-mitigation-multiple-choice
82. wang-2024-browse-concentrate-comprehending-multimodal-content
83. wang-2024-smarttrim-adaptive-tokens-attention-pruning
84. wu-2023-lilgym-natural-language-visual-reasoning
85. wu-2024-vdebugger-harnessing-execution-feedback-debugging
86. wu-2025-glyphpattern-abstract-pattern-recognition-vision
87. xu-2023-managertower-aggregating-insights-uni-modal
88. xu-2024-multiskill-evaluating-large-multimodal-models
89. yanaka-2023-medical-visual-textual-entailment-numerical
90. zhang-2023-building-general-foundation-models-language
91. zhao-2025-realbench-chinese-multi-image-understanding
92. zhu-2022-generalization-differences-between-end-end

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