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

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

Pages: 1 · 2

  1. Biases in Large Language Model-Elicited Text: A Case Study in Natural Language Inference — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
  2. Elements of World Knowledge ( EWoK ): A Cognition-Inspired Framework for Evaluating Basic World Knowledge in Language Models — 2025
  3. Artifacts or Abduction: How Do LLMs Answer Multiple-Choice Questions Without the Question? — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  4. Desiderata For The Context Use Of Question Answering Systems — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  5. HAE-RAE Bench: Evaluation of Korean Knowledge in Language Models — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  6. Hypothesis-only Biases in Large Language Model-Elicited Natural Language Inference — 2024 · arXiv:2410.08996
  7. Measuring and Improving Attentiveness to Partial Inputs with Counterfactuals — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  8. Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries — 2024 · arXiv:2409.12640
  9. RAZOR: Sharpening Knowledge by Cutting Bias with Unsupervised Text Rewriting — 2024 · arXiv:2412.07675
  10. Towards Faithful Model Explanation in NLP: A Survey — 2024 · Computational Linguistics
  11. 大语言模型故事理解能力评价数据集(Benchmarking story comprehension ability of large language model) — 2024 · Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference)
  12. DISCO: Distilling Counterfactuals with Large Language Models — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  13. Evaluation for Change — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  14. Fighting Bias With Bias: Promoting Model Robustness by Amplifying Dataset Biases — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  15. GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-Distribution Generalization Perspective — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  16. Investigating UD Treebanks via Dataset Difficulty Measures — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  17. It Takes Two to Tango: Navigating Conceptualizations of NLP Tasks and Measurements of Performance — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  18. Maximum Entropy Loss, the Silver Bullet Targeting Backdoor Attacks in Pre-trained Language Models — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  19. Out-of-Distribution Generalization in Natural Language Processing: Past, Present, and Future — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  20. Question-Answering in a Low-resourced Language: Benchmark Dataset and Models for Tigrinya — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  21. SkillQG: Learning to Generate Question for Reading Comprehension Assessment — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  22. What's the Meaning of Superhuman Performance in Today's NLU? — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  23. When and Why Does Bias Mitigation Work? — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  24. ``World Knowledge'''' in Multiple Choice Reading Comprehension — 2023 · Proceedings of the Sixth Fact Extraction and VERification Workshop (FEVER)
  25. A Few More Examples May Be Worth Billions of Parameters — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  26. A Generative Approach for Mitigating Structural Biases in Natural Language Inference — 2022 · Proceedings of the 11th Joint Conference on Lexical and Computational Semantics
  27. Breakpoint Transformers for Modeling and Tracking Intermediate Beliefs — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  28. CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about Negation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  29. CQG: A Simple and Effective Controlled Generation Framework for Multi-hop Question Generation — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  30. Cascading Biases: Investigating the Effect of Heuristic Annotation Strategies on Data and Models — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  31. Challenges in Generalization in Open Domain Question Answering — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
  32. Does Your Model Classify Entities Reasonably? Diagnosing and Mitigating Spurious Correlations in Entity Typing — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  33. Dyna-bAbI: unlocking bAbI''s potential with dynamic synthetic benchmarking — 2022 · Proceedings of the 11th Joint Conference on Lexical and Computational Semantics
  34. LogicNMR: Probing the Non-monotonic Reasoning Ability of Pre-trained Language Models — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  35. Machine Reading, Fast and Slow: When Do Models ``Understand'''' Language? — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  36. MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  37. On the Robustness of Reading Comprehension Models to Entity Renaming — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  38. Partial-input baselines show that NLI models can ignore context, but they don't. — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  39. State-of-the-art generalisation research in NLP: A taxonomy and review — 2022 · arXiv:2210.03050 · Nat Mach Intell 5, 1161-1174 (2023)
  40. Text-based NP Enrichment — 2022 · Transactions of the Association for Computational Linguistics
  41. What Makes Reading Comprehension Questions Difficult? — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  42. Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  43. Back to Square One: Artifact Detection, Training and Commonsense Disentanglement in the Winograd Schema — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  44. Benchmarking Machine Reading Comprehension: A Psychological Perspective — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
  45. Benchmarking Robustness of Machine Reading Comprehension Models — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  46. COM2SENSE: A Commonsense Reasoning Benchmark with Complementary Sentences — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  47. Challenges in Information-Seeking QA: Unanswerable Questions and Paragraph Retrieval — 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)
  48. Diagnosing the First-Order Logical Reasoning Ability Through LogicNLI — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  49. DynaSent: A Dynamic Benchmark for Sentiment Analysis — 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)
  50. Exploring Strategies for Generalizable Commonsense Reasoning with Pre-trained Models — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  51. Hurdles to Progress in Long-form Question Answering — 2021 · arXiv:2103.06332
  52. NOAHQA: Numerical Reasoning with Interpretable Graph Question Answering Dataset — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
  53. On the Efficacy of Adversarial Data Collection for Question Answering: Results from a Large-Scale Randomized Study — 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)
  54. On the Interplay Between Fine-tuning and Composition in Transformers — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  55. Probing the Probing Paradigm: Does Probing Accuracy Entail Task Relevance? — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
  56. Question and Answer Test-Train Overlap in Open-Domain Question Answering Datasets — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
  57. Robust Question Answering Through Sub-part Alignment — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  58. Sensitivity as a Complexity Measure for Sequence Classification Tasks — 2021 · Transactions of the Association for Computational Linguistics
  59. Shortcutted Commonsense: Data Spuriousness in Deep Learning of Commonsense Reasoning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  60. Towards Domain-Generalizable Paraphrase Identification by Avoiding the Shortcut Learning — 2021 · Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2021)
  61. What Ingredients Make for an Effective Crowdsourcing Protocol for Difficult NLU Data Collection Tasks? — 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)
  62. Why Machine Reading Comprehension Models Learn Shortcuts? — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  63. 基于篇章结构攻击的阅读理解任务探究(Analysis of Reading Comprehension Tasks based on passage structure attacks) — 2021 · Proceedings of the 20th Chinese National Conference on Computational Linguistics
  64. A Framework for Evaluation of Machine Reading Comprehension Gold Standards — 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference
  65. Adversarial NLI: A New Benchmark for Natural Language Understanding — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  66. Are Pretrained Language Models Symbolic Reasoners over Knowledge? — 2020 · Proceedings of the 24th Conference on Computational Natural Language Learning
  67. Are we Estimating or Guesstimating Translation Quality? — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  68. Beat the AI: Investigating Adversarial Human Annotation for Reading Comprehension — 2020
  69. Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models — 2020 · arXiv:2005.14709
  70. Controlled Hallucinations: Learning to Generate Faithfully from Noisy Data — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  71. Counterfactual Generator: A Weakly-Supervised Method for Named Entity Recognition — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  72. Data and its (dis)contents: A survey of dataset development and use in machine learning research — 2020 · arXiv:2012.05345 · Patterns, Volume 2, Issue 11, 100336. 2021
  73. Do We Need to Create Big Datasets to Learn a Task? — 2020 · Proceedings of SustaiNLP: Workshop on Simple and Efficient Natural Language Processing
  74. End-to-End Bias Mitigation by Modelling Biases in Corpora — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  75. How do Decisions Emerge across Layers in Neural Models? Interpretation with Differentiable Masking — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  76. HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data — 2020 · arXiv:2004.07347
  77. Intrinsic Evaluation of Summarization Datasets — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  78. MUTANT: A Training Paradigm for Out-of-Distribution Generalization in Visual Question Answering — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  79. On the Cross-lingual Transferability of Monolingual Representations — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  80. On the Systematicity of Probing Contextualized Word Representations: The Case of Hypernymy in BERT — 2020 · Proceedings of the Ninth Joint Conference on Lexical and Computational Semantics
  81. Self-Supervised Knowledge Triplet Learning for Zero-Shot Question Answering — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  82. Shortcut Learning in Deep Neural Networks — 2020 · arXiv:2004.07780
  83. The Curse of Performance Instability in Analysis Datasets: Consequences, Source, and Suggestions — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  84. The Sensitivity of Language Models and Humans to Winograd Schema Perturbations — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  85. To Test Machine Comprehension, Start by Defining Comprehension — 2020 · arXiv:2005.01525
  86. Towards Debiasing NLU Models from Unknown Biases — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  87. Translation Artifacts in Cross-lingual Transfer Learning — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  88. What Question Answering can Learn from Trivia Nerds — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  89. What do we expect from Multiple-choice QA Systems? — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  90. Adversarial Regularization for Visual Question Answering: Strengths, Shortcomings, and Side Effects — 2019 · Proceedings of the Second Workshop on Shortcomings in Vision and Language
  91. Assessing the Benchmarking Capacity of Machine Reading Comprehension Datasets — 2019 · arXiv:1911.09241
  92. Bend but Don't Break? Multi-Challenge Stress Test for QA Models — 2019 · Proceedings of the 2nd Workshop on Machine Reading for Question Answering
  93. 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)
  94. 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)
  95. 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
  96. Evidence Sentence Extraction for Machine Reading Comprehension — 2019 · Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)
  97. HEAD-QA: A Healthcare Dataset for Complex Reasoning — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
  98. 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)
  99. 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)
  100. 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

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