Elamur Research
☰
home / papers / RACE: Large-scale ReAding Comprehension Dataset… / cited by

Who cites «RACE: Large-scale ReAding Comprehension Dataset From Examinations» · page 6

617 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 · 7

  1. Improving QA Generalization by Concurrent Modeling of Multiple Biases — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  2. LEGAL-BERT: The Muppets straight out of Law School — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  3. Language Models are Few-Shot Learners — 2020 · arXiv:2005.14165
  4. LiveQA: A Question Answering Dataset over Sports Live — 2020 · Proceedings of the 19th Chinese National Conference on Computational Linguistics
  5. LogiQA: A Challenge Dataset for Machine Reading Comprehension with Logical Reasoning — 2020 · arXiv:2007.08124
  6. 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)
  7. MPNet: Masked and Permuted Pre-training for Language Understanding — 2020 · arXiv:2004.09297
  8. Measuring Massive Multitask Language Understanding — 2020 · arXiv:2009.03300
  9. Memory-Efficient Pipeline-Parallel DNN Training — 2020 · ICML 2021
  10. Molweni: A Challenge Multiparty Dialogues-based Machine Reading Comprehension Dataset with Discourse Structure — 2020 · Proceedings of the 28th International Conference on Computational Linguistics
  11. MuTual: A Dataset for Multi-Turn Dialogue Reasoning — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  12. Multi-source Meta Transfer for Low Resource Multiple-Choice Question Answering — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  13. NUT-RC: Noisy User-generated Text-oriented Reading Comprehension — 2020 · Proceedings of the 28th International Conference on Computational Linguistics
  14. Optimal Subarchitecture Extraction For BERT — 2020 · arXiv:2010.10499
  15. PRover: Proof Generation for Interpretable Reasoning over Rules — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  16. Question Directed Graph Attention Network for Numerical Reasoning over Text — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  17. ReClor: A Reading Comprehension Dataset Requiring Logical Reasoning — 2020 · arXiv:2002.04326
  18. Read and Reason with MuSeRC and RuCoS: Datasets for Machine Reading Comprehension for Russian — 2020 · Proceedings of the 28th International Conference on Computational Linguistics
  19. Revisiting Pre-Trained Models for Chinese Natural Language Processing — 2020 · arXiv:2004.13922
  20. SCDE: Sentence Cloze Dataset with High Quality Distractors From Examinations — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  21. STARC: Structured Annotations for Reading Comprehension — our card · 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  22. Scalable Multi-Hop Relational Reasoning for Knowledge-Aware Question Answering — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  23. ScholarlyRead: A New Dataset for Scientific Article Reading Comprehension — 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference
  24. Seeing the World through Text: Evaluating Image Descriptions for Commonsense Reasoning in Machine Reading Comprehension — 2020 · Proceedings of the Second Workshop on Beyond Vision and LANguage: inTEgrating Real-world kNowledge (LANTERN)
  25. To Test Machine Comprehension, Start by Defining Comprehension — 2020 · arXiv:2005.01525
  26. Towards Medical Machine Reading Comprehension with Structural Knowledge and Plain Text — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  27. Transfer Learning from Transformers to Fake News Challenge Stance Detection (FNC-1) Task — 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference
  28. Transformers as Soft Reasoners over Language — 2020 · arXiv:2002.05867
  29. UNIFIEDQA: Crossing Format Boundaries with a Single QA System — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  30. UPB at SemEval-2020 Task 8: Joint Textual and Visual Modeling in a Multi-Task Learning Architecture for Memotion Analysis — 2020 · Proceedings of the Fourteenth Workshop on Semantic Evaluation
  31. Unsupervised Domain Adaptation of Language Models for Reading Comprehension — 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference
  32. What Disease does this Patient Have? A Large-scale Open Domain Question Answering Dataset from Medical Exams — 2020 · arXiv:2009.13081
  33. What Does My QA Model Know? Devising Controlled Probes Using Expert Knowledge — 2020 · Transactions of the Association for Computational Linguistics
  34. What do we expect from Multiple-choice QA Systems? — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  35. Which *BERT? A Survey Organizing Contextualized Encoders — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  36. ``You are grounded!'''': Latent Name Artifacts in Pre-trained Language Models — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  37. 基于深度学习的语言模型研究进展 — 2020 · 软件学报 (Journal of Software)
  38. 基于神经网络的机器阅读理解综述 — 2020 · 软件学报 (Journal of Software)
  39. 多模块联合的阅读理解候选句抽取(Evidence sentence extraction for reading comprehension based on multi-module) — 2020 · Proceedings of the 19th Chinese National Conference on Computational Linguistics
  40. An Exploration of Data Augmentation and Sampling Techniques for Domain-Agnostic Question Answering — 2019 · Proceedings of the 2nd Workshop on Machine Reading for Question Answering
  41. Answering questions by learning to rank - Learning to rank by answering questions — 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)
  42. Assessing the Benchmarking Capacity of Machine Reading Comprehension Datasets — 2019 · arXiv:1911.09241
  43. BERT Post-Training for Review Reading Comprehension and Aspect-based Sentiment Analysis — 2019 · arXiv:1904.02232
  44. Beyond English-Only Reading Comprehension: Experiments in Zero-shot Multilingual Transfer for Bulgarian — 2019 · Proceedings of the International Conference on Recent Advances in Natural Language Processing (RANLP 2019)
  45. BiPaR: A Bilingual Parallel Dataset for Multilingual and Cross-lingual Reading Comprehension on Novels — 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)
  46. BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions — 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)
  47. CJRC: A Reliable Human-Annotated Benchmark DataSet for Chinese Judicial Reading Comprehension — 2019 · arXiv:1912.09156
  48. CLER: Cross-task Learning with Expert Representation to Generalize Reading and Understanding — 2019 · Proceedings of the 2nd Workshop on Machine Reading for Question Answering
  49. Careful Selection of Knowledge to Solve Open Book Question Answering — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
  50. ChID: A Large-scale Chinese IDiom Dataset for Cloze Test — 2019 · arXiv:1906.01265
  51. Cosmos QA: Machine Reading Comprehension with Contextual Commonsense Reasoning — our card · 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)
  52. Dialog State Tracking: A Neural Reading Comprehension Approach — 2019 · Proceedings of the 20th Annual SIGdial Meeting on Discourse and Dialogue
  53. Domain-agnostic Question-Answering with Adversarial Training — 2019 · Proceedings of the 2nd Workshop on Machine Reading for Question Answering
  54. Evaluating Commonsense in Pre-trained Language Models — 2019 · arXiv:1911.11931
  55. Evidence Sentence Extraction for Machine Reading Comprehension — 2019 · Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL)
  56. Finding Generalizable Evidence by Learning to Convince Q&A 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)
  57. FreeLB: Enhanced Adversarial Training for Natural Language Understanding — 2019 · arXiv:1909.11764
  58. FriendsQA: Open-Domain Question Answering on TV Show Transcripts — 2019 · Proceedings of the 20th Annual SIGdial Meeting on Discourse and Dialogue
  59. From ''F'' to ''A'' on the N.Y. Regents Science Exams: An Overview of the Aristo Project — 2019 · arXiv:1909.01958
  60. GeoSQA: A Benchmark for Scenario-based Question Answering in the Geography Domain at High School Level — 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)
  61. HEAD-QA: A Healthcare Dataset for Complex Reasoning — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
  62. IIT-KGP at COIN 2019: Using pre-trained Language Models for modeling Machine Comprehension — 2019 · Proceedings of the First Workshop on Commonsense Inference in Natural Language Processing
  63. 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)
  64. 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
  65. Investigating Prior Knowledge for Challenging Chinese Machine Reading Comprehension — 2019 · arXiv:1904.09679
  66. JEC-QA: A Legal-Domain Question Answering Dataset — 2019 · arXiv:1911.12011
  67. Jeff Da at COIN - Shared Task: BIG MOOD: Relating Transformers to Explicit Commonsense Knowledge — 2019 · Proceedings of the First Workshop on Commonsense Inference in Natural Language Processing
  68. KagNet: Knowledge-Aware Graph Networks for Commonsense 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)
  69. Learning to Attend On Essential Terms: An Enhanced Retriever-Reader Model for Open-domain Question Answering — 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)
  70. MCScript2.0: A Machine Comprehension Corpus Focused on Script Events and Participants — 2019 · Proceedings of the Eighth Joint Conference on Lexical and Computational Semantics (*SEM 2019)
  71. Megatron-LM: Training Multi-Billion Parameter Language Models Using Model Parallelism — 2019 · arXiv:1909.08053
  72. MultiQA: An Empirical Investigation of Generalization and Transfer in Reading Comprehension — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
  73. Natural Questions: A Benchmark for Question Answering Research — 2019
  74. 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)
  75. Patient Knowledge Distillation for BERT Model Compression — 2019 · arXiv:1908.09355
  76. 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
  77. QASC: A Dataset for Question Answering via Sentence Composition — 2019 · arXiv:1910.11473
  78. QuaRTz: An Open-Domain Dataset of Qualitative Relationship Questions — 2019 · arXiv:1909.03553
  79. Question Answering by Reasoning Across Documents with Graph Convolutional Networks — 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)
  80. 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)
  81. Quoref: A Reading Comprehension Dataset with Questions Requiring Coreferential Reasoning — our card · 2019 · arXiv:1908.05803
  82. Recent Advances in Natural Language Inference: A Survey of Benchmarks, Resources, and Approaches — 2019 · arXiv:1904.01172
  83. 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)
  84. RoBERTa: A Robustly Optimized BERT Pretraining Approach — 2019 · arXiv:1907.11692
  85. TWEETQA: A Social Media Focused Question Answering Dataset — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
  86. Towards Generalizable Neuro-Symbolic Systems for Commonsense Question Answering — 2019 · Proceedings of the First Workshop on Commonsense Inference in Natural Language Processing
  87. 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)
  88. XLNet: Generalized Autoregressive Pretraining for Language Understanding — 2019 · arXiv:1906.08237
  89. 基於特徵粒度之訓練策略於中文口語問答系統之應用 (A Feature-granularity Training Strategy for Chinese Spoken Question Answering) — 2019
  90. A Co-Matching Model for Multi-choice Reading Comprehension — 2018 · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
  91. A Span-Extraction Dataset for Chinese Machine Reading Comprehension — 2018 · arXiv:1810.07366 · EMNLP 2019 5886-5891
  92. Challenging Reading Comprehension on Daily Conversation: Passage Completion on Multiparty Dialog — 2018 · Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
  93. DARC-IT: a DAtaset for Reading Comprehension in ITalian — 2018 · Proceedings of the Fifth Italian Conference on Computational Linguistics (CLiC-it 2018)
  94. DRCD: a Chinese Machine Reading Comprehension Dataset — 2018 · arXiv:1806.00920
  95. DuoRC: Towards Complex Language Understanding with Paraphrased Reading Comprehension — 2018 · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  96. ECNU at SemEval-2018 Task 11: Using Deep Learning Method to Address Machine Comprehension Task — 2018 · Proceedings of the 12th International Workshop on Semantic Evaluation
  97. Efficient and Robust Question Answering from Minimal Context over Documents — 2018 · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  98. How Much Reading Does Reading Comprehension Require? A Critical Investigation of Popular Benchmarks — our card · 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
  99. Know What You Don''t Know: Unanswerable Questions for SQuAD — 2018 · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
  100. Large-scale Cloze Test Dataset Created by Teachers — 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing

Pages: 1 · 2 · 3 · 4 · 5 · 6 · 7