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# Who cites «MCTest: A Challenge Dataset for the Open-Domain Machine Comprehension of Text» · page 3

263 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/missing-2013-richardson-mctest-challenge-dataset-open-domain/)

Pages: [1](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/missing-2013-richardson-mctest-challenge-dataset-open-domain/) · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/missing-2013-richardson-mctest-challenge-dataset-open-domain-2/) · **3**

1. [Learning To Use Formulas To Solve Simple Arithmetic Problems](https://md.mova.elamur.ai/free/en/docs/papers/mitra-2016-learning-use-formulas-solve-simple/) *— our card · 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
2. [MAWPS: A Math Word Problem Repository](https://aclanthology.org/N16-1136/) *— 2016 · Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies*
3. [Machine Comprehension Using Match-LSTM and Answer Pointer](https://arxiv.org/abs/1608.07905) *— 2016 · arXiv:1608.07905*
4. [Machine Comprehension using Rich Semantic Representations](https://aclanthology.org/P16-2079/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
5. [SQuAD: 100,000+ Questions for Machine Comprehension of Text](https://aclanthology.org/D16-1264/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
6. [Science Question Answering using Instructional Materials](https://aclanthology.org/P16-2076/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)*
7. [Text Understanding with the Attention Sum Reader Network](https://aclanthology.org/P16-1086/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
8. [The LAMBADA dataset: Word prediction requiring a broad discourse context](https://aclanthology.org/P16-1144/) *— 2016 · Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)*
9. [Understanding Satirical Articles Using Common-Sense](https://aclanthology.org/Q16-1038/) *— 2016 · Transactions of the Association for Computational Linguistics*
10. [Who did What: A Large-Scale Person-Centered Cloze Dataset](https://aclanthology.org/D16-1241/) *— 2016 · Proceedings of the 2016 Conference on Empirical Methods in Natural Language Processing*
11. [A Strong Lexical Matching Method for the Machine Comprehension Test](https://aclanthology.org/D15-1197/) *— 2015 · Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing*
12. [Learning Answer-Entailing Structures for Machine Comprehension](https://aclanthology.org/P15-1024/) *— 2015 · Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
13. [Machine Comprehension with Discourse Relations](https://aclanthology.org/P15-1121/) *— 2015 · Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)*
14. [Machine Comprehension with Syntax, Frames, and Semantics](https://aclanthology.org/P15-2115/) *— 2015 · Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers)*
15. [Teaching Machines to Read and Comprehend](https://arxiv.org/abs/1506.03340) *— 2015 · arXiv:1506.03340*
16. [The Goldilocks Principle: Reading Children''s Books with Explicit Memory Representations](https://arxiv.org/abs/1511.02301) *— 2015 · arXiv:1511.02301*
17. [Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks](https://md.mova.elamur.ai/free/en/docs/papers/weston-2015-towards-ai-complete-question-answering/) *— our card · 2015 · arXiv:1502.05698*
18. [Fact Checking: Task definition and dataset construction](https://aclanthology.org/W14-2508/) *— 2014 · Proceedings of the ACL 2014 Workshop on Language Technologies and Computational Social Science*
19. [Memory Networks](https://arxiv.org/abs/1410.3916) *— 2014 · arXiv:1410.3916*
20. [Modeling Biological Processes for Reading Comprehension](https://aclanthology.org/D14-1159/) *— 2014 · Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)*
21. [Animacy Detection with Voting Models](https://aclanthology.org/D13-1006/) *— 2013 · Proceedings of the 2013 Conference on Empirical Methods in Natural Language Processing*
22. aksu-2021-velocidapter-task-oriented-dialogue-comprehension
23. bakhshandeh-2017-apples-apples-learning-semantics-common
24. balepur-2026-benchmarker-education-inspired-toolkit-highlighting
25. bansal-2023-few-shot-unified-question-answering
26. byun-2025-textit-d-gen-automatic-distractor
27. do-2023-machine-reading-comprehension-vietnamese-customer
28. girgis-2021-latent-variable-sequential-set-transformers
29. goyal-2018-think-visually-question-answering-through
30. grail-2018-adversarial-networks-machine-reading
31. jiang-2018-csreader-semeval-2018-task-11
32. lei-2024-qsnail-questionnaire-dataset-sequential-question
33. liu-2021-unsupervised-multiple-choices-question-answering
34. luo-2023-explicit-alignment-many-many-entailment
35. majumder-2021-model-agnostic-answer-reranking-system
36. meyur-2025-weqa-benchmark-retrieval-augmented-generation
37. nakanishi-2018-answerable-or-not-devising-dataset
38. peng-2020-bi-directional-cognitivethinking-network-machine
39. pezeshkpour-2024-large-language-models-sensitivity-order
40. sakamoto-2025-development-numerical-error-detection-tasks
41. saraswat-2024-story-yarn-interactive-story-building
42. seo-2025-feat-preference-feedback-dataset-through
43. sharma-2019-iit-kgp-coin-2019-pre
44. sosa-2019-active-reading-comprehension-dataset-learning
45. stanovsky-2015-open-ie-as-intermediate-structure
46. sun-2022-improving-machine-reading-comprehension-contextualized
47. thai-2023-machine-reading-comprehension-case-based
48. urbizu-2025-sub-1b-language-models-low
49. vatsal-2024-can-gpt-redefine-medical-understanding
50. veyseh-2022-behanceqa-new-dataset-identifying-question
51. wang-2024-information-theoretic-approach-analyze-nlp
52. watarai-2020-developing-dataset-japanese-slot-filling
53. xiao-2025-scop-evaluating-comprehension-process-large
54. xiaoyan-2021-multi-strategy-knowledge-distillation-based
55. yadav-2017-learning-knowledge-transfer-memory-networks
56. yao-2022-corpus-commonsense-inference-story-cloze
57. yoon-2023-diversity-enhanced-narrative-question-generation
58. zhang-2021-knowledge-empowered-representation-learning-chinese
59. zhang-2022-hrca-advanced-multiple-choice-machine
60. zhang-2024-interpreting-themes-educational-stories
61. zhao-2023-parrot-zero-shot-narrative-reading
62. zhixing-2021-topic-knowledge-acquisition-utilization-machine
63. zhu-2022-answer-quality-aware-aggregation-extractive

Pages: [1](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/missing-2013-richardson-mctest-challenge-dataset-open-domain/) · [2](https://md.mova.elamur.ai/free/en/docs/papers/cited-by/missing-2013-richardson-mctest-challenge-dataset-open-domain-2/) · **3**

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