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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

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  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. CURE: Controlled Unlearning for Robust Embeddings –- Mitigating Conceptual Shortcuts in Pre-Trained Language Models — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
  3. Elements of World Knowledge ( EWoK ): A Cognition-Inspired Framework for Evaluating Basic World Knowledge in Language Models — 2025
  4. Task Calibration: Calibrating Large Language Models on Inference Tasks — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  5. 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)
  6. 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)
  7. 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)
  8. Hypothesis-only Biases in Large Language Model-Elicited Natural Language Inference — 2024 · arXiv:2410.08996
  9. Measuring and Improving Attentiveness to Partial Inputs with Counterfactuals — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  10. Michelangelo: Long Context Evaluations Beyond Haystacks via Latent Structure Queries — 2024 · arXiv:2409.12640
  11. Pointing Out the Shortcomings of Relation Extraction Models with Semantically Motivated Adversarials — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  12. RAZOR: Sharpening Knowledge by Cutting Bias with Unsupervised Text Rewriting — 2024 · arXiv:2412.07675
  13. Towards Faithful Model Explanation in NLP: A Survey — 2024 · Computational Linguistics
  14. 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)
  15. DISCO: Distilling Counterfactuals with Large Language Models — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  16. Evaluation for Change — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  17. Explanation-based Finetuning Makes Models More Robust to Spurious Cues — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  18. Fighting Bias With Bias: Promoting Model Robustness by Amplifying Dataset Biases — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  19. GLUE-X: Evaluating Natural Language Understanding Models from an Out-of-Distribution Generalization Perspective — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  20. Investigating UD Treebanks via Dataset Difficulty Measures — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  21. It Takes Two to Tango: Navigating Conceptualizations of NLP Tasks and Measurements of Performance — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  22. Maximum Entropy Loss, the Silver Bullet Targeting Backdoor Attacks in Pre-trained Language Models — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  23. Multimodal Graph Transformer for Multimodal Question Answering — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  24. On Degrees of Freedom in Defining and Testing Natural Language Understanding — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  25. 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
  26. 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)
  27. Real-Time Visual Feedback to Guide Benchmark Creation: A Human-and-Metric-in-the-Loop Workflow — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  28. SkillQG: Learning to Generate Question for Reading Comprehension Assessment — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  29. 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)
  30. When and Why Does Bias Mitigation Work? — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  31. ``World Knowledge'''' in Multiple Choice Reading Comprehension — 2023 · Proceedings of the Sixth Fact Extraction and VERification Workshop (FEVER)
  32. A Few More Examples May Be Worth Billions of Parameters — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  33. A Generative Approach for Mitigating Structural Biases in Natural Language Inference — 2022 · Proceedings of the 11th Joint Conference on Lexical and Computational Semantics
  34. Breakpoint Transformers for Modeling and Tracking Intermediate Beliefs — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  35. CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about Negation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  36. 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)
  37. Can Edge Probing Tests Reveal Linguistic Knowledge in QA Models? — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  38. 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
  39. Challenges in Generalization in Open Domain Question Answering — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
  40. 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
  41. Dyna-bAbI: unlocking bAbI''s potential with dynamic synthetic benchmarking — 2022 · Proceedings of the 11th Joint Conference on Lexical and Computational Semantics
  42. Leveraging Expert Guided Adversarial Augmentation For Improving Generalization in Named Entity Recognition — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  43. LogicNMR: Probing the Non-monotonic Reasoning Ability of Pre-trained Language Models — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  44. Machine Reading, Fast and Slow: When Do Models ``Understand'''' Language? — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  45. 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)
  46. 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
  47. 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
  48. State-of-the-art generalisation research in NLP: A taxonomy and review — 2022 · arXiv:2210.03050 · Nat Mach Intell 5, 1161-1174 (2023)
  49. Text-based NP Enrichment — 2022 · Transactions of the Association for Computational Linguistics
  50. What Makes Reading Comprehension Questions Difficult? — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  51. AutoEQA: Auto-Encoding Questions for Extractive Question Answering — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
  52. Avoiding Inference Heuristics in Few-shot Prompt-based Finetuning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  53. 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
  54. 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
  55. Benchmarking Robustness of Machine Reading Comprehension Models — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  56. COM2SENSE: A Commonsense Reasoning Benchmark with Complementary Sentences — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  57. 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)
  58. Diagnosing the First-Order Logical Reasoning Ability Through LogicNLI — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  59. 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)
  60. Exploring Strategies for Generalizable Commonsense Reasoning with Pre-trained Models — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  61. GANDALF: a General Character Name Description Dataset for Long Fiction — 2021 · Proceedings of the 3rd Workshop on Machine Reading for Question Answering
  62. Hurdles to Progress in Long-form Question Answering — 2021 · arXiv:2103.06332
  63. Model Agnostic Answer Reranking System for Adversarial Question Answering — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop
  64. NOAHQA: Numerical Reasoning with Interpretable Graph Question Answering Dataset — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
  65. 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)
  66. On the Interplay Between Fine-tuning and Composition in Transformers — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  67. On the Transferability of Minimal Prediction Preserving Inputs in Question Answering — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  68. 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
  69. 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
  70. 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
  71. Sensitivity as a Complexity Measure for Sequence Classification Tasks — 2021 · Transactions of the Association for Computational Linguistics
  72. Shortcutted Commonsense: Data Spuriousness in Deep Learning of Commonsense Reasoning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  73. 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)
  74. 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)
  75. Why Machine Reading Comprehension Models Learn Shortcuts? — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  76. 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
  77. A Framework for Evaluation of Machine Reading Comprehension Gold Standards — 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference
  78. Adversarial NLI: A New Benchmark for Natural Language Understanding — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  79. Are Pretrained Language Models Symbolic Reasoners over Knowledge? — 2020 · Proceedings of the 24th Conference on Computational Natural Language Learning
  80. Are we Estimating or Guesstimating Translation Quality? — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  81. Avoiding the Hypothesis-Only Bias in Natural Language Inference via Ensemble Adversarial Training — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  82. Beat the AI: Investigating Adversarial Human Annotation for Reading Comprehension — 2020
  83. Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models — 2020 · arXiv:2005.14709
  84. Controlled Hallucinations: Learning to Generate Faithfully from Noisy Data — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  85. Counterfactual Generator: A Weakly-Supervised Method for Named Entity Recognition — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  86. 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
  87. Developing Dataset of Japanese Slot Filling Quizzes Designed for Evaluation of Machine Reading Comprehension — 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference
  88. Do We Need to Create Big Datasets to Learn a Task? — 2020 · Proceedings of SustaiNLP: Workshop on Simple and Efficient Natural Language Processing
  89. End-to-End Bias Mitigation by Modelling Biases in Corpora — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  90. 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)
  91. HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data — 2020 · arXiv:2004.07347
  92. Intrinsic Evaluation of Summarization Datasets — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  93. MRC Examples Answerable by BERT without a Question Are Less Effective in MRC Model Training — 2020 · Proceedings of the 1st Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 10th International Joint Conference on Natural Language Processing: Student Research Workshop
  94. 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)
  95. On the Cross-lingual Transferability of Monolingual Representations — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  96. 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
  97. Self-Supervised Knowledge Triplet Learning for Zero-Shot Question Answering — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  98. Shortcut Learning in Deep Neural Networks — 2020 · arXiv:2004.07780
  99. 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)
  100. The Sensitivity of Language Models and Humans to Winograd Schema Perturbations — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics

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