Mova0.5 pre-release⌕
☰
home / docs / papers / cited-by / Who cites «RACE: Large-scale ReAding Comprehension Dataset From Examinations» · page 3

Who cites «RACE: Large-scale ReAding Comprehension Dataset From Examinations» · page 3

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. ``World Knowledge'''' in Multiple Choice Reading Comprehension — 2023 · Proceedings of the Sixth Fact Extraction and VERification Workshop (FEVER)
  2. An MRC Framework for Semantic Role Labeling — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  3. Analyzing Multi-Task Learning for Abstractive Text Summarization — 2022 · Proceedings of the Second Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)
  4. Answer Uncertainty and Unanswerability in Multiple-Choice Machine Reading Comprehension — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  5. Atlas: Few-shot Learning with Retrieval Augmented Language Models — 2022 · arXiv:2208.03299
  6. BBQ: A hand-built bias benchmark for question answering — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  7. BanglaRQA: A Benchmark Dataset for Under-resourced Bangla Language Reading Comprehension-based Question Answering with Diverse Question-Answer Types — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  8. Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language models — 2022 · arXiv:2206.04615 · Transactions on Machine Learning Research, May/2022, https://openreview.net/forum?id=uyTL5Bvosj
  9. CONDAQA: A Contrastive Reading Comprehension Dataset for Reasoning about Negation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  10. 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
  11. Case-Based Abductive Natural Language Inference — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  12. Compliance Checking with NLI: Privacy Policies vs. Regulations — 2022 · arXiv:2204.01845
  13. ConfliBERT: A Pre-trained Language Model for Political Conflict and Violence — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  14. Data Augmentation for Biomedical Factoid Question Answering — 2022 · Proceedings of the 21st Workshop on Biomedical Language Processing
  15. DeepSpeed-MoE: Advancing Mixture-of-Experts Inference and Training to Power Next-Generation AI Scale — 2022 · arXiv:2201.05596
  16. Discovering Language Model Behaviors with Model-Written Evaluations — 2022 · arXiv:2212.09251
  17. Document-level Event Factuality Identification via Machine Reading Comprehension Frameworks with Transfer Learning — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  18. E-KAR: A Benchmark for Rationalizing Natural Language Analogical Reasoning — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  19. Editing Models with Task Arithmetic — 2022 · arXiv:2212.04089
  20. Eliciting and Understanding Cross-task Skills with Task-level Mixture-of-Experts — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  21. Evaluating the Knowledge Dependency of Questions — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  22. Exploring The Landscape of Distributional Robustness for Question Answering Models — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  23. FQuAD2.0: French Question Answering and Learning When You Don''t Know — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
  24. Fantastic Questions and Where to Find Them: FairytaleQA – An Authentic Dataset for Narrative Comprehension — our card · 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  25. Feeding What You Need by Understanding What You Learned — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  26. Fine- and Coarse-Granularity Hybrid Self-Attention for Efficient BERT — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  27. Hyperdecoders: Instance-specific decoders for multi-task NLP — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  28. KECP: Knowledge Enhanced Contrastive Prompting for Few-shot Extractive Question Answering — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  29. Leveraging Large Language Models for Multiple Choice Question Answering — 2022 · arXiv:2210.12353
  30. Life after BERT: What do Other Muppets Understand about Language? — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  31. LogiTorch: A PyTorch-based library for logical reasoning on natural language — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: System Demonstrations
  32. Logic Traps in Evaluating Attribution Scores — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  33. MoEfication: Transformer Feed-forward Layers are Mixtures of Experts — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  34. Modeling Hierarchical Reasoning Chains by Linking Discourse Units and Key Phrases for Reading Comprehension — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  35. OPERA: Operation-Pivoted Discrete Reasoning over Text — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  36. PILE: Pairwise Iterative Logits Ensemble for Multi-Teacher Labeled Distillation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track
  37. PPT: Pre-trained Prompt Tuning for Few-shot Learning — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  38. PaLM: Scaling Language Modeling with Pathways — 2022 · arXiv:2204.02311
  39. Perturbation Augmentation for Fairer NLP — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  40. Possible Stories: Evaluating Situated Commonsense Reasoning under Multiple Possible Scenarios — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  41. ProQA: Structural Prompt-based Pre-training for Unified Question Answering — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  42. QAConv: Question Answering on Informative Conversations — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  43. QuALITY: Question Answering with Long Input Texts, Yes! — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  44. Question Answering Infused Pre-training of General-Purpose Contextualized Representations — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  45. RealTime QA: What''s the Answer Right Now? — 2022 · arXiv:2207.13332
  46. Retrieval Augmentation for Commonsense Reasoning: A Unified Approach — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  47. SPoT: Better Frozen Model Adaptation through Soft Prompt Transfer — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  48. Scaling Laws Under the Microscope: Predicting Transformer Performance from Small Scale Experiments — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  49. Self-critiquing models for assisting human evaluators — 2022 · arXiv:2206.05802
  50. Synthetic Data Generation for Multilingual Domain-Adaptable Question Answering Systems — 2022 · Proceedings of the 23rd Annual Conference of the European Association for Machine Translation
  51. TIE: Topological Information Enhanced Structural Reading Comprehension on Web Pages — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  52. To Answer or Not To Answer? Improving Machine Reading Comprehension Model with Span-based Contrastive Learning — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
  53. Training Compute-Optimal Large Language Models — 2022 · arXiv:2203.15556
  54. UKP-SQUARE: An Online Platform for Question Answering Research — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
  55. UL2: Unifying Language Learning Paradigms — 2022 · arXiv:2205.05131
  56. Using DeepSpeed and Megatron to Train Megatron-Turing NLG 530B, A Large-Scale Generative Language Model — 2022 · arXiv:2201.11990
  57. Vector-Quantized Input-Contextualized Soft Prompts for Natural Language Understanding — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  58. What Language Model Architecture and Pretraining Objective Work Best for Zero-Shot Generalization? — 2022 · arXiv:2204.05832
  59. What Language Model to Train if You Have One Million GPU Hours? — 2022 · arXiv:2210.15424
  60. What Makes Reading Comprehension Questions Difficult? — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  61. Zero-Shot Learners for Natural Language Understanding via a Unified Multiple Choice Perspective — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  62. ZeroQuant: Efficient and Affordable Post-Training Quantization for Large-Scale Transformers — 2022 · arXiv:2206.01861
  63. `Am I the Bad One''? Predicting the Moral Judgement of the Crowd Using Pre–trained Language Models — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
  64. 基于相似度进行句子选择的机器阅读理解数据增强(Machine reading comprehension data Augmentation for sentence selection based on similarity) — 2022 · Proceedings of the 21st Chinese National Conference on Computational Linguistics
  65. A Robustly Optimized BERT Pre-training Approach with Post-training — 2021 · Proceedings of the 20th Chinese National Conference on Computational Linguistics
  66. Arabic Offensive Language on Twitter: Analysis and Experiments — 2021 · Proceedings of the Sixth Arabic Natural Language Processing Workshop
  67. Asking Questions Like Educational Experts: Automatically Generating Question-Answer Pairs on Real-World Examination Data — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  68. 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
  69. Benchmarking Robustness of Machine Reading Comprehension Models — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  70. CLEVR_HYP: A Challenge Dataset and Baselines for Visual Question Answering with Hypothetical Actions over Images — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  71. CTAL: Pre-training Cross-modal Transformer for Audio-and-Language Representations — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  72. CodeQA: A Question Answering Dataset for Source Code Comprehension — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
  73. Comparing Test Sets with Item Response Theory — 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)
  74. 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)
  75. Controlling Text Edition by Changing Answers of Specific Questions — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  76. CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP — 2021 · arXiv:2104.08835
  77. DeBERTaV3: Improving DeBERTa using ELECTRA-Style Pre-Training with Gradient-Disentangled Embedding Sharing — 2021 · arXiv:2111.09543
  78. Diagnosing the First-Order Logical Reasoning Ability Through LogicNLI — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  79. English Machine Reading Comprehension Datasets: A Survey — our card · 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  80. Evaluation Paradigms in Question Answering — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  81. ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning — 2021 · arXiv:2111.10952
  82. Explaining NLP Models via Minimal Contrastive Editing (MiCE) — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  83. Extract, Integrate, Compete: Towards Verification Style Reading Comprehension — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
  84. Few Shot Dialogue State Tracking using Meta-learning — 2021 · Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
  85. GCRC: A New Challenging MRC Dataset from Gaokao Chinese for Explainable Evaluation — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  86. GLaM: Efficient Scaling of Language Models with Mixture-of-Experts — 2021 · arXiv:2112.06905
  87. General-Purpose Question-Answering with Macaw — 2021 · arXiv:2109.02593
  88. How Can We Know When Language Models Know? On the Calibration of Language Models for Question Answering — 2021
  89. Learning from Limited Labels for Long Legal Dialogue — 2021 · Proceedings of the Natural Legal Language Processing Workshop 2021
  90. 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
  91. Memory-efficient Transformers via Top-k Attention — 2021 · Proceedings of the Second Workshop on Simple and Efficient Natural Language Processing
  92. MetaICL: Learning to Learn In Context — 2021 · arXiv:2110.15943
  93. MinD at SemEval-2021 Task 6: Propaganda Detection using Transfer Learning and Multimodal Fusion — 2021 · Proceedings of the 15th International Workshop on Semantic Evaluation (SemEval-2021)
  94. Multi-tasking Dialogue Comprehension with Discourse Parsing — 2021 · Proceedings of the 35th Pacific Asia Conference on Language, Information and Computation
  95. Multitask Prompted Training Enables Zero-Shot Task Generalization — 2021 · arXiv:2110.08207
  96. Muppet: Massive Multi-task Representations with Pre-Finetuning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  97. 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
  98. NOAHQA: Numerical Reasoning with Interpretable Graph Question Answering Dataset — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
  99. 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
  100. 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)

Pages: 1 · 2 · 3 · 4 · 5 · 6 · 7

This page in Markdown → https://md.mova.elamur.ai/free/en/docs/papers/cited-by/lai-2017-race-large-scale-reading-comprehension-3/