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Who cites «How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks» · page 2

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

Pages: 1 · 2

  1. To Test Machine Comprehension, Start by Defining Comprehension — 2020 · arXiv:2005.01525
  2. Towards Debiasing NLU Models from Unknown Biases — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  3. Translation Artifacts in Cross-lingual Transfer Learning — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  4. What Question Answering can Learn from Trivia Nerds — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  5. What do we expect from Multiple-choice QA Systems? — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  6. WikiPossessions: Possession Timeline Generation as an Evaluation Benchmark for Machine Reading Comprehension of Long Texts — 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference
  7. Adversarial Regularization for Visual Question Answering: Strengths, Shortcomings, and Side Effects — 2019 · Proceedings of the Second Workshop on Shortcomings in Vision and Language
  8. Assessing the Benchmarking Capacity of Machine Reading Comprehension Datasets — 2019 · arXiv:1911.09241
  9. Bend but Don't Break? Multi-Challenge Stress Test for QA Models — 2019 · Proceedings of the 2nd Workshop on Machine Reading for Question Answering
  10. CLUTRR: A Diagnostic Benchmark for Inductive Reasoning from Text — 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. DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs — our card · 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
  12. Don''t Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
  13. Evidence Sentence Extraction for Machine Reading Comprehension — 2019 · Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)
  14. HEAD-QA: A Healthcare Dataset for Complex Reasoning — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
  15. Harry Potter and the Action Prediction Challenge from Natural Language — 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
  16. Identifying Supporting Facts for Multi-hop Question Answering with Document Graph Networks — 2019 · Proceedings of the Thirteenth Workshop on Graph-Based Methods for Natural Language Processing (TextGraphs-13)
  17. Inferring Which Medical Treatments Work from Reports of Clinical Trials — 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
  18. Is It Dish Washer Safe? Automatically Answering ``Yes/No'' Questions Using Customer Reviews — 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Student Research Workshop
  19. Learning Latent Parameters without Human Response Patterns: Item Response Theory with Artificial Crowds — 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)
  20. Learning the Difference that Makes a Difference with Counterfactually-Augmented Data — 2019 · arXiv:1909.12434
  21. Measuring text readability with machine comprehension: a pilot study — 2019 · Proceedings of the Fourteenth Workshop on Innovative Use of NLP for Building Educational Applications
  22. Misleading Failures of Partial-input Baselines — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
  23. Neural Text Summarization: A Critical Evaluation — 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)
  24. NumNet: Machine Reading Comprehension with Numerical Reasoning — 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)
  25. Pingan Smart Health and SJTU at COIN - Shared Task: utilizing Pre-trained Language Models and Common-sense Knowledge in Machine Reading Tasks — 2019 · Proceedings of the First Workshop on Commonsense Inference in Natural Language Processing
  26. Question Answering for Privacy Policies: Combining Computational and Legal Perspectives — 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)
  27. Quoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning — our card · 2019 · arXiv:1908.05803
  28. Shifting the Baseline: Single Modality Performance on Visual Navigation & QA — 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
  29. Towards Debiasing Fact Verification Models — 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)
  30. Understanding Dataset Design Choices for Multi-hop Reasoning — 2019 · Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers)
  31. Unlearn Dataset Bias in Natural Language Inference by Fitting the Residual — 2019 · Proceedings of the 2nd Workshop on Deep Learning Approaches for Low-Resource NLP (DeepLo 2019)
  32. Unsupervised Question Answering by Cloze Translation — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
  33. ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension — 2018 · arXiv:1810.12885

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