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home / docs / papers / cited-by / Who cites «Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences» · page 2

Who cites «Looking Beyond the Surface: A Challenge Set for Reading Comprehension over Multiple Sentences» · page 2

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

Pages: 1 · 2 · 3

  1. UPRISE: Universal Prompt Retrieval for Improving Zero-Shot Evaluation — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  2. UltraFeedback: Boosting Language Models with Scaled AI Feedback — 2023 · arXiv:2310.01377
  3. Understanding the Role of Input Token Characters in Language Models: How Does Information Loss Affect Performance? — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  4. Unsupervised Selective Rationalization with Noise Injection — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  5. Vote''n''Rank: Revision of Benchmarking with Social Choice Theory — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  6. Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision — 2023 · arXiv:2312.09390
  7. 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)
  8. When Your Language Model Cannot Even Do Determiners Right: Probing for Anti-Presuppositions and the Maximize Presupposition! Principle — our card · 2023 · Proceedings of the 6th BlackboxNLP Workshop: Analyzing and Interpreting Neural Networks for NLP
  9. Where to start? Analyzing the potential value of intermediate models — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  10. ACES: Translation Accuracy Challenge Sets for Evaluating Machine Translation Metrics — our card · 2022 · Proceedings of the Seventh Conference on Machine Translation (WMT)
  11. ATTEMPT: Parameter-Efficient Multi-task Tuning via Attentional Mixtures of Soft Prompts — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  12. AdapLeR: Speeding up Inference by Adaptive Length Reduction — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  13. An Investigation of the (In)effectiveness of Counterfactually Augmented Data — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  14. Analyzing Multi-Task Learning for Abstractive Text Summarization — 2022 · Proceedings of the Second Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)
  15. Ask Me Anything: A simple strategy for prompting language models — 2022 · arXiv:2210.02441
  16. 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
  17. Can Rationalization Improve Robustness? — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  18. Cross-Task Generalization via Natural Language Crowdsourcing Instructions — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  19. Design Challenges for a Multi-Perspective Search Engine — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
  20. Double Trouble: How to not Explain a Text Classifier''s Decisions Using Counterfactuals Synthesized by Masked Language Models? — 2022 · Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)
  21. Down and Across: Introducing Crossword-Solving as a New NLP Benchmark — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  22. Eliciting and Understanding Cross-task Skills with Task-level Mixture-of-Experts — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  23. FewNLU: Benchmarking State-of-the-Art Methods for Few-Shot Natural Language Understanding — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  24. FlipDA: Effective and Robust Data Augmentation for Few-Shot Learning — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  25. Hey AI, Can You Solve Complex Tasks by Talking to Agents? — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  26. Human-Centered Evaluation of Explanations — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies: Tutorial Abstracts
  27. Improving In-Context Few-Shot Learning via Self-Supervised Training — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  28. Is a Question Decomposition Unit All We Need? — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  29. Learning to Perform Complex Tasks through Compositional Fine-Tuning of Language Models — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  30. Locate Then Ask: Interpretable Stepwise Reasoning for Multi-hop Question Answering — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  31. On the Diversity and Limits of Human Explanations — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  32. Reframing Instructional Prompts to GPTk's Language — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  33. 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)
  34. Towards a Unified Multi-Dimensional Evaluator for Text Generation — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  35. Transferring Confluent Knowledge to Argument Mining — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  36. UKP-SQUARE: An Online Platform for Question Answering Research — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
  37. UNIREX: A Unified Learning Framework for Language Model Rationale Extraction — 2022 · Proceedings of BigScience Episode \#5 – Workshop on Challenges & Perspectives in Creating Large Language Models
  38. Vector-Quantized Input-Contextualized Soft Prompts for Natural Language Understanding — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  39. What Language Model Architecture and Pretraining Objective Work Best for Zero-Shot Generalization? — 2022 · arXiv:2204.05832
  40. What Language Model to Train if You Have One Million GPU Hours? — 2022 · arXiv:2210.15424
  41. What Makes Reading Comprehension Questions Difficult? — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  42. What to Learn, and How: Toward Effective Learning from Rationales — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  43. Word Order Does Matter and Shuffled Language Models Know It — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  44. XPrompt: Exploring the Extreme of Prompt Tuning — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  45. 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
  46. 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
  47. Beyond Reptile: Meta-Learned Dot-Product Maximization between Gradients for Improved Single-Task Regularization — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
  48. 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)
  49. 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)
  50. CrossFit: A Few-shot Learning Challenge for Cross-task Generalization in NLP — 2021 · arXiv:2104.08835
  51. 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
  52. Did Aristotle Use a Laptop? A Question Answering Benchmark with Implicit Reasoning Strategies — 2021
  53. 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
  54. ERNIE 3.0: Large-scale Knowledge Enhanced Pre-training for Language Understanding and Generation — 2021 · arXiv:2107.02137
  55. English Machine Reading Comprehension Datasets: A Survey — our card · 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  56. 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
  57. Evaluation Paradigms in Question Answering — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  58. ExT5: Towards Extreme Multi-Task Scaling for Transfer Learning — 2021 · arXiv:2111.10952
  59. FiD-Ex: Improving Sequence-to-Sequence Models for Extractive Rationale Generation — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  60. Finetuned Language Models Are Zero-Shot Learners — 2021 · arXiv:2109.01652
  61. GCRC: A New Challenging MRC Dataset from Gaokao Chinese for Explainable Evaluation — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  62. GLaM: Efficient Scaling of Language Models with Mixture-of-Experts — 2021 · arXiv:2112.06905
  63. GPT Understands, Too — 2021 · arXiv:2103.10385
  64. 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
  65. 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
  66. 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
  67. 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
  68. Measuring Association Between Labels and Free-Text Rationales — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  69. MetaICL: Learning to Learn In Context — 2021 · arXiv:2110.15943
  70. Multitask Prompted Training Enables Zero-Shot Task Generalization — 2021 · arXiv:2110.08207
  71. Muppet: Massive Multi-task Representations with Pre-Finetuning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  72. 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
  73. 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
  74. REPT: Bridging Language Models and Machine Reading Comprehension via Retrieval-Based Pre-training — 2021 · Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
  75. 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
  76. 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
  77. The Power of Scale for Parameter-Efficient Prompt Tuning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  78. True Few-Shot Learning with Language Models — 2021 · arXiv:2105.11447
  79. UNICORN on RAINBOW: A Universal Commonsense Reasoning Model on a New Multitask Benchmark — 2021 · arXiv:2103.13009
  80. What to Pre-Train on? Efficient Intermediate Task Selection — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  81. A Diagnostic Study of Explainability Techniques for Text Classification — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  82. A Framework for Evaluation of Machine Reading Comprehension Gold Standards — 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference
  83. 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
  84. An Information Bottleneck Approach for Controlling Conciseness in Rationale Extraction — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  85. 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
  86. DeBERTa: Decoding-enhanced BERT with Disentangled Attention — 2020 · arXiv:2006.03654
  87. ERASER: A Benchmark to Evaluate Rationalized NLP Models — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  88. Evaluating and Characterizing Human Rationales — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  89. Event Coreference Resolution with their Paraphrases and Argument-aware Embeddings — 2020 · Proceedings of the 28th International Conference on Computational Linguistics
  90. HoVer: A Dataset for Many-Hop Fact Extraction And Claim Verification — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  91. 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)
  92. INFOTABS: Inference on Tables as Semi-structured Data — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  93. 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
  94. 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)
  95. Language Models are Few-Shot Learners — 2020 · arXiv:2005.14165
  96. Learning from Task Descriptions — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  97. Learning to Faithfully Rationalize by Construction — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  98. Linguistic Appropriateness and Pedagogic Usefulness of Reading Comprehension Questions — 2020 · Proceedings of the Twelfth Language Resources and Evaluation Conference
  99. 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)
  100. 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)

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