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Who cites «Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences» · page 3

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

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  1. Beyond Reptile: Meta-Learned Dot-Product Maximization between Gradients for Improved Single-Task Regularization — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
  2. Conditional Generation of Temporally-ordered Event Sequences — 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)
  3. Coreference Reasoning in Machine Reading Comprehension — 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)
  4. CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP — 2021 · arXiv:2104.08835
  5. DAGN: Discourse-Aware Graph Network for Logical Reasoning — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  6. Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies — 2021
  7. Discrete Reasoning Templates for Natural Language Understanding — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop
  8. Do Multi-Hop Question Answering Systems Know How to Answer the Single-Hop Sub-Questions? — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
  9. ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation — 2021 · arXiv:2107.02137
  10. English Machine Reading Comprehension Datasets: A Survey — our card · 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  11. Enhancing Multiple-choice Machine Reading Comprehension by Punishing Illogical Interpretations — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  12. Enjoy the Salience: Towards Better Transformer-based Faithful Explanations with Word Salience — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  13. Evaluation Paradigms in Question Answering — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  14. ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning — 2021 · arXiv:2111.10952
  15. FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  16. Finetuned Language Models Are Zero-Shot Learners — 2021 · arXiv:2109.01652
  17. GANDALF: a General Character Name Description Dataset for Long Fiction — 2021 · Proceedings of the 3rd Workshop on Machine Reading for Question Answering
  18. GCRC: A New Challenging MRC Dataset from Gaokao Chinese for Explainable Evaluation — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  19. GLaM: Efficient Scaling of Language Models with Mixture-of-Experts — 2021 · arXiv:2112.06905
  20. GPT Understands, Too — 2021 · arXiv:2103.10385
  21. How many data points is a prompt worth? — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  22. If You Want to Go Far Go Together: Unsupervised Joint Candidate Evidence Retrieval for Multi-hop Question Answering — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  23. It''s Not Just Size That Matters: Small Language Models Are Also Few-Shot Learners — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  24. Looking Beyond Sentence-Level Natural Language Inference for Question Answering and Text Summarization — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  25. Measuring Association Between Labels and Free-Text Rationales — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  26. MetaICL: Learning to Learn In Context — 2021 · arXiv:2110.15943
  27. Multitask Prompted Training Enables Zero-Shot Task Generalization — 2021 · arXiv:2110.08207
  28. Muppet: Massive Multi-task Representations with Pre-Finetuning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  29. On the Challenges of Evaluating Compositional Explanations in Multi-Hop Inference: Relevance, Completeness, and Expert Ratings — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  30. Paragraph-level Rationale Extraction through Regularization: A case study on European Court of Human Rights Cases — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  31. REPT: Bridging Language Models and Machine Reading Comprehension via Retrieval-Based Pre-training — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  32. SPARTQA: A Textual Question Answering Benchmark for Spatial Reasoning — our card · 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  33. Shatter: An Efficient Transformer Encoder with Single-Headed Self-Attention and Relative Sequence Partitioning — 2021 · arXiv:2108.13032
  34. Text Modular Networks: Learning to Decompose Tasks in the Language of Existing Models — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  35. The Power of Scale for Parameter-Efficient Prompt Tuning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  36. True Few-Shot Learning with Language Models — 2021 · arXiv:2105.11447
  37. UNICORN on RAINBOW: A Universal Commonsense Reasoning Model on a New Multitask Benchmark — 2021 · arXiv:2103.13009
  38. Unsupervised Multiple Choices Question Answering: Start Learning from Basic Knowledge — 2021 · Proceedings of the 3rd Workshop on Machine Reading for Question Answering
  39. What to Pre-Train on? Efficient Intermediate Task Selection — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  40. A Diagnostic Study of Explainability Techniques for Text Classification — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  41. A Framework for Evaluation of Machine Reading Comprehension Gold Standards — 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference
  42. A Self-Training Method for Machine Reading Comprehension with Soft Evidence Extraction — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  43. An Information Bottleneck Approach for Controlling Conciseness in Rationale Extraction — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  44. Asking Crowdworkers to Write Entailment Examples: The Best of Bad Options — 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
  45. DeBERTa: Decoding-enhanced BERT with Disentangled Attention — 2020 · arXiv:2006.03654
  46. ERASER: A Benchmark to Evaluate Rationalized NLP Models — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  47. Evaluating and Characterizing Human Rationales — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  48. Event Coreference Resolution with their Paraphrases and Argument-aware Embeddings — 2020 · Proceedings of the 28th International Conference on Computational Linguistics
  49. HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  50. How Much Knowledge Can You Pack Into the Parameters of a Language Model? — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  51. INFOTABS: Inference on Tables as Semi-structured Data — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  52. Intermediate-Task Transfer Learning with Pretrained Language Models: When and Why Does It Work? — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  53. Is Multihop QA in DiRe Condition? Measuring and Reducing Disconnected Reasoning — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  54. Language Models are Few-Shot Learners — 2020 · arXiv:2005.14165
  55. Learning from Task Descriptions — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  56. Learning to Faithfully Rationalize by Construction — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  57. Linguistic Appropriateness and Pedagogic Usefulness of Reading Comprehension Questions — 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference
  58. MOCHA: A Dataset for Training and Evaluating Generative Reading Comprehension Metrics — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  59. More Bang for Your Buck: Natural Perturbation for Robust Question Answering — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  60. MuTual: A Dataset for Multi-Turn Dialogue Reasoning — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  61. Multi-source Meta Transfer for Low Resource Multiple-Choice Question Answering — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  62. New Protocols and Negative Results for Textual Entailment Data Collection — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  63. Optimal Subarchitecture Extraction For BERT — 2020 · arXiv:2010.10499
  64. Overview of the SustaiNLP 2020 Shared Task — 2020 · Proceedings of SustaiNLP: Workshop on Simple and Efficient Natural Language Processing
  65. PGL at TextGraphs 2020 Shared Task: Explanation Regeneration using Language and Graph Learning Methods — 2020 · Proceedings of the Graph-based Methods for Natural Language Processing (TextGraphs)
  66. Rationalizing Text Matching: Learning Sparse Alignments via Optimal Transport — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  67. ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning — 2020 · arXiv:2002.04326
  68. Read and Reason with MuSeRC and RuCoS: Datasets for Machine Reading Comprehension for Russian — 2020 · Proceedings of the 28th International Conference on Computational Linguistics
  69. RussianSuperGLUE: A Russian Language Understanding Evaluation Benchmark — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  70. STARC: Structured Annotations for Reading Comprehension — our card · 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  71. To Test Machine Comprehension, Start by Defining Comprehension — 2020 · arXiv:2005.01525
  72. UNIFIEDQA: Crossing Format Boundaries with a Single QA System — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  73. Unsupervised Alignment-based Iterative Evidence Retrieval for Multi-hop Question Answering — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  74. Which *BERT? A Survey Organizing Contextualized Encoders — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  75. Why do you think that? Exploring Faithful Sentence-Level Rationales Without Supervision — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  76. A Qualitative Comparison of CoQA, SQuAD 2.0 and QuAC — 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)
  77. Answering while Summarizing: Multi-task Learning for Multi-hop QA with Evidence Extraction — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
  78. Assessing the Benchmarking Capacity of Machine Reading Comprehension Datasets — 2019 · arXiv:1911.09241
  79. DREAM: A Challenge Data Set and Models for Dialogue-Based Reading Comprehension — 2019 · Transactions of the Association for Computational Linguistics
  80. 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)
  81. Evidence Sentence Extraction for Machine Reading Comprehension — 2019 · Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)
  82. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer — 2019 · arXiv:1910.10683
  83. Improving Machine Reading Comprehension with General Reading Strategies — 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)
  84. Inferential Machine Comprehension: Answering Questions by Recursively Deducing the Evidence Chain from Text — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
  85. Investigating Prior Knowledge for Challenging Chinese Machine Reading Comprehension — 2019 · arXiv:1904.09679
  86. Multi-hop Reading Comprehension across Multiple Documents by Reasoning over Heterogeneous Graphs — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
  87. QASC: A Dataset for Question Answering via Sentence Composition — 2019 · arXiv:1910.11473
  88. Quick and (not so) Dirty: Unsupervised Selection of Justification Sentences for Multi-hop Question Answering — 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)
  89. Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches — 2019 · arXiv:1904.01172
  90. Repurposing Entailment for Multi-Hop Question Answering Tasks — 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)
  91. Revisiting Joint Modeling of Cross-document Entity and Event Coreference Resolution — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
  92. SuperGLUE: A Stickier Benchmark for General-Purpose Language Understanding Systems — 2019 · arXiv:1905.00537
  93. 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)
  94. Using Natural Language Relations between Answer Choices for Machine Comprehension — 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. What''s Missing: A Knowledge Gap Guided Approach for Multi-hop Question Answering — 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)
  96. ``Going on a vacation'''' takes longer than ``Going for a walk'''': A Study of Temporal Commonsense Understanding — 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)
  97. Can a Suit of Armor Conduct Electricity? A New Dataset for Open Book Question Answering — 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
  98. Multi-Relational Question Answering from Narratives: Machine Reading and Reasoning in Simulated Worlds — our card · 2018 · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  99. What Makes Reading Comprehension Questions Easier? — 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

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