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home / docs / papers / cited-by / Who cites «DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs» · page 4

Who cites «DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs» · page 4

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

Pages: 1 · 2 · 3 · 4 · 5 · 6

  1. Turning Tables: Generating Examples from Semi-structured Tables for Endowing Language Models with Reasoning Skills — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  2. UKP-SQUARE: An Online Platform for Question Answering Research — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
  3. Understand before Answer: Improve Temporal Reading Comprehension via Precise Question Understanding — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  4. Understanding and Improving Zero-shot Multi-hop Reasoning in Generative Question Answering — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  5. UniRPG: Unified Discrete Reasoning over Table and Text as Program Generation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  6. Vector-Quantized Input-Contextualized Soft Prompts for Natural Language Understanding — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  7. What Makes Reading Comprehension Questions Difficult? — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  8. A Dataset for Answering Time-Sensitive Questions — 2021 · arXiv:2108.06314
  9. A Dataset of Information-Seeking Questions and Answers Anchored in Research Papers — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  10. A Mutual Information Maximization Approach for the Spurious Solution Problem in Weakly Supervised Question Answering — 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)
  11. 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
  12. Benchmarking Robustness of Machine Reading Comprehension Models — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  13. COM2SENSE: A Commonsense Reasoning Benchmark with Complementary Sentences — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  14. 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)
  15. Competency Problems: On Finding and Removing Artifacts in Language Data — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  16. Constrained Language Models Yield Few-Shot Semantic Parsers — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  17. Contrasting Human- and Machine-Generated Word-Level Adversarial Examples for Text Classification — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  18. Controllable Open-ended Question Generation with A New Question Type Ontology — 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)
  19. 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)
  20. 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
  21. Database reasoning over text — 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)
  22. Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies — 2021
  23. Distantly-Supervised Dense Retrieval Enables Open-Domain Question Answering without Evidence Annotation — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  24. 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)
  25. Dynabench: Rethinking Benchmarking in NLP — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  26. English Machine Reading Comprehension Datasets: A Survey — our card · 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  27. Evaluating Entity Disambiguation and the Role of Popularity in Retrieval-Based NLP — 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)
  28. Evaluation Paradigms in Question Answering — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  29. ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning — 2021 · arXiv:2111.10952
  30. Few-Shot Question Answering by Pretraining Span Selection — 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)
  31. FinQA: A Dataset of Numerical Reasoning over Financial Data — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  32. Finetuned Language Models Are Zero-Shot Learners — 2021 · arXiv:2109.01652
  33. ForecastQA: A Question Answering Challenge for Event Forecasting with Temporal Text Data — 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)
  34. GLaM: Efficient Scaling of Language Models with Mixture-of-Experts — 2021 · arXiv:2112.06905
  35. Have You Seen That Number? Investigating Extrapolation in Question Answering Models — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  36. How Fast can BERT Learn Simple Natural Language Inference? — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
  37. Improving Question Answering Model Robustness with Synthetic Adversarial Data Generation — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  38. Investigating Numeracy Learning Ability of a Text-to-Text Transfer Model — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
  39. Investigating the Limitations of Transformers with Simple Arithmetic Tasks — 2021 · arXiv:2102.13019
  40. Learning by Fixing: Solving Math Word Problems with Weak Supervision — 2021 · AAAI 2021 (arXiv 2012.10582)
  41. Learning from Limited Labels for Long Legal Dialogue — 2021 · Proceedings of the Natural Legal Language Processing Workshop 2021
  42. MetaICL: Learning to Learn In Context — 2021 · arXiv:2110.15943
  43. Multitask Prompted Training Enables Zero-Shot Task Generalization — 2021 · arXiv:2110.08207
  44. Muppet: Massive Multi-task Representations with Pre-Finetuning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  45. NLQuAD: A Non-Factoid Long Question Answering Data Set — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
  46. NOAHQA: Numerical Reasoning with Interpretable Graph Question Answering Dataset — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
  47. Numerical reasoning in machine reading comprehension tasks: are we there yet? — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  48. 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)
  49. Paired Examples as Indirect Supervision in Latent Decision Models — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  50. REPT: Bridging Language Models and Machine Reading Comprehension via Retrieval-Based Pre-training — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  51. Reliability Testing for Natural Language Processing Systems — 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)
  52. Representing Numbers in NLP: a Survey and a Vision — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  53. 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
  54. SPARQLing Database Queries from Intermediate Question Decompositions — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  55. SPARTA: Efficient Open-Domain Question Answering via Sparse Transformer Matching Retrieval — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  56. 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
  57. Shortcutted Commonsense: Data Spuriousness in Deep Learning of Commonsense Reasoning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  58. Single-dataset Experts for Multi-dataset Question Answering — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  59. SituatedQA: Incorporating Extra-Linguistic Contexts into QA — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  60. Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answering — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  61. TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Finance — 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. Team Papelo at FEVEROUS: Multi-hop Evidence Pursuit — 2021 · Proceedings of the Fourth Workshop on Fact Extraction and VERification (FEVER)
  63. 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
  64. The Power of Scale for Parameter-Efficient Prompt Tuning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  65. Time-Stamped Language Model: Teaching Language Models to Understand The Flow of Events — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  66. 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)
  67. What to Pre-Train on? Efficient Intermediate Task Selection — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  68. What's in Your Head? Emergent Behaviour in Multi-Task Transformer Models — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  69. What's in a Name? Answer Equivalence For Open-Domain Question Answering — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  70. Why Machine Reading Comprehension Models Learn Shortcuts? — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  71. A Dataset for Statutory Reasoning in Tax Law Entailment and Question Answering — 2020 · arXiv:2005.05257
  72. A Framework for Evaluation of Machine Reading Comprehension Gold Standards — 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference
  73. A Simple and Effective Model for Answering Multi-span Questions — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  74. A Vietnamese Dataset for Evaluating Machine Reading Comprehension — 2020 · Proceedings of the 28th International Conference on Computational Linguistics
  75. A guide to the dataset explosion in QA, NLI, and commonsense reasoning — our card · 2020 · Proceedings of the 28th International Conference on Computational Linguistics: Tutorial Abstracts
  76. An Empirical Investigation of Contextualized Number Prediction — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  77. Are Pretrained Language Models Symbolic Reasoners over Knowledge? — 2020 · Proceedings of the 24th Conference on Computational Natural Language Learning
  78. Ask to Learn: A Study on Curiosity-driven Question Generation — 2020 · Proceedings of the 28th International Conference on Computational Linguistics
  79. Beat the AI: Investigating Adversarial Human Annotation for Reading Comprehension — 2020
  80. Benefits of Intermediate Annotations in Reading Comprehension — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  81. Beyond Leaderboards: A survey of methods for revealing weaknesses in Natural Language Inference data and models — 2020 · arXiv:2005.14709
  82. Birds have four legs?! NumerSense: Probing Numerical Commonsense Knowledge of Pre-Trained Language Models — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  83. Break It Down: A Question Understanding Benchmark — 2020 · Transactions of the Association for Computational Linguistics
  84. CAiRE-COVID: A Question Answering and Query-focused Multi-Document Summarization System for COVID-19 Scholarly Information Management — 2020 · Proceedings of the 1st Workshop on NLP for COVID-19 (Part 2) at EMNLP 2020
  85. Climbing towards NLU: On Meaning, Form, and Understanding in the Age of Data — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  86. Compositional Generalization in Semantic Parsing: Pre-training vs. Specialized Architectures — 2020 · arXiv:2007.08970
  87. DeSePtion: Dual Sequence Prediction and Adversarial Examples for Improved Fact-Checking — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  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. Dynamic Sampling Strategies for Multi-Task Reading Comprehension — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  90. Easy, Reproducible and Quality-Controlled Data Collection with CROWDAQ — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
  91. Evaluating Models' Local Decision Boundaries via Contrast Sets — our card · 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  92. Exploring and Predicting Transferability across NLP Tasks — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  93. 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)
  94. HybridQA: A Dataset of Multi-Hop Question Answering over Tabular and Textual Data — 2020 · arXiv:2004.07347
  95. IIRC: A Dataset of Incomplete Information Reading Comprehension Questions — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  96. Improving Compositional Generalization in Semantic Parsing — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  97. Improving QA Generalization by Concurrent Modeling of Multiple Biases — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  98. Injecting Numerical Reasoning Skills into Language Models — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  99. Language (Re)modelling: Towards Embodied Language Understanding — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  100. Language Models are Few-Shot Learners — 2020 · arXiv:2005.14165

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