Mova0.5 pre-release⌕
☰
home / docs / papers / cited-by / Who cites «DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs» · page 3

Who cites «DROP: A Reading Comprehension Benchmark Requiring Discrete Reasoning Over Paragraphs» · page 3

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. Long-Tailed Question Answering in an Open World — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  2. MAF: Multi-Aspect Feedback for Improving Reasoning in Large Language Models — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  3. MAFiD: Moving Average Equipped Fusion-in-Decoder for Question Answering over Tabular and Textual Data — 2023 · Findings of the Association for Computational Linguistics: EACL 2023
  4. Making Language Models Better Reasoners with Step-Aware Verifier — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  5. MarkQA: A large scale KBQA dataset with numerical reasoning — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  6. MatCha: Enhancing Visual Language Pretraining with Math Reasoning and Chart Derendering — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  7. MetaMath: Bootstrap Your Own Mathematical Questions for Large Language Models — 2023 · arXiv:2309.12284
  8. MoT: Memory-of-Thought Enables ChatGPT to Self-Improve — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  9. Multi-Row, Multi-Span Distant Supervision For Table+Text Question Answering — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  10. Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future — 2023 · arXiv:2309.15402
  11. Numeric Magnitude Comparison Effects in Large Language Models — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  12. Orca 2: Teaching Small Language Models How to Reason — 2023 · arXiv:2311.11045
  13. PaLM 2 Technical Report — 2023 · arXiv:2305.10403
  14. Post-Abstention: Towards Reliably Re-Attempting the Abstained Instances in QA — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  15. Prompting with Pseudo-Code Instructions — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  16. RA-DIT: Retrieval-Augmented Dual Instruction Tuning — 2023 · arXiv:2310.01352
  17. RQUGE: Reference-Free Metric for Evaluating Question Generation by Answering the Question — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  18. ReCEval: Evaluating Reasoning Chains via Correctness and Informativeness — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  19. Reasoning over Public and Private Data in Retrieval-Based Systems — 2023 · Transactions of the Association for Computational Linguistics
  20. Robust Prompt Optimization for Large Language Models Against Distribution Shifts — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  21. SEER : A Knapsack approach to Exemplar Selection for In-Context HybridQA — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  22. SlideVQA: A Dataset for Document Visual Question Answering on Multiple Images — 2023 · arXiv:2301.04883
  23. Tab-CQA: A Tabular Conversational Question Answering Dataset on Financial Reports — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 5: Industry Track)
  24. Unifying Structure Reasoning and Language Model Pre-training for Complex Reasoning — 2023 · arXiv:2301.08913
  25. VILA: On Pre-training for Visual Language Models — 2023 · arXiv:2312.07533
  26. Weakly-Supervised Questions for Zero-Shot Relation Extraction — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  27. When Do Decompositions Help for Machine Reading? — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  28. ZO-AdaMU Optimizer: Adapting Perturbation by the Momentum and Uncertainty in Zeroth-order Optimization — 2023 · arXiv:2312.15184
  29. ``John is 50 years old, can his son be 65?'''' Evaluating NLP Models'' Understanding of Feasibility — 2023 · Proceedings of the 17th Conference of the European Chapter of the Association for Computational Linguistics
  30. A Few More Examples May Be Worth Billions of Parameters — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  31. ANLIzing the Adversarial Natural Language Inference Dataset — 2022 · Proceedings of the Society for Computation in Linguistics 2022
  32. AdaLoGN: Adaptive Logic Graph Network for Reasoning-Based Machine Reading Comprehension — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  33. Addressing Resource and Privacy Constraints in Semantic Parsing Through Data Augmentation — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  34. An MRC Framework for Semantic Role Labeling — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  35. Analytical Reasoning of Text — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
  36. Analyzing Dynamic Adversarial Training Data in the Limit — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  37. Analyzing Multi-Task Learning for Abstractive Text Summarization — 2022 · Proceedings of the Second Workshop on Natural Language Generation, Evaluation, and Metrics (GEM)
  38. Answering Numerical Reasoning Questions in Table-Text Hybrid Contents with Graph-based Encoder and Tree-based Decoder — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  39. Ask Me Anything: A simple strategy for prompting language models — 2022 · arXiv:2210.02441
  40. 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
  41. 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
  42. ByT5: Towards a Token-Free Future with Pre-trained Byte-to-Byte Models — 2022
  43. CMQA: A Dataset of Conditional Question Answering with Multiple-Span Answers — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  44. Case-Based Abductive Natural Language Inference — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  45. Chaining Simultaneous Thoughts for Numerical Reasoning — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  46. Challenges in Generalization in Open Domain Question Answering — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
  47. CommonsenseQA 2.0: Exposing the Limits of AI through Gamification — 2022 · arXiv:2201.05320
  48. Complex Reading Comprehension Through Question Decomposition — 2022 · Proceedings of the 20th Annual Workshop of the Australasian Language Technology Association
  49. ConvFinQA: Exploring the Chain of Numerical Reasoning in Conversational Finance Question Answering — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  50. 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)
  51. Curriculum: A Broad-Coverage Benchmark for Linguistic Phenomena in Natural Language Understanding — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  52. Domain Adaptation for Question Answering via Question Classification — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  53. Efficient Training of Language Models to Fill in the Middle — 2022 · arXiv:2207.14255
  54. Efficiently Tuned Parameters Are Task Embeddings — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  55. Enhancing Financial Table and Text Question Answering with Tabular Graph and Numerical Reasoning — 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)
  56. Exploiting Numerical-Contextual Knowledge to Improve Numerical Reasoning in Question Answering — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
  57. Exploring The Landscape of Distributional Robustness for Question Answering Models — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  58. FORTAP: Using Formulas for Numerical-Reasoning-Aware Table Pretraining — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  59. FQuAD2.0: French Question Answering and Learning When You Don''t Know — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
  60. Generalized Quantifiers as a Source of Error in Multilingual NLU Benchmarks — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  61. Hey AI, Can You Solve Complex Tasks by Talking to Agents? — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  62. Hyperdecoders: Instance-specific decoders for multi-task NLP — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  63. Identifying Weaknesses in Machine Translation Metrics Through Minimum Bayes Risk Decoding: A Case Study for COMET — 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)
  64. Impact of Pretraining Term Frequencies on Few-Shot Numerical Reasoning — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  65. 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
  66. Interpretable Proof Generation via Iterative Backward Reasoning — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  67. Is a Question Decomposition Unit All We Need? — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  68. LILA: A Unified Benchmark for Mathematical Reasoning — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  69. Learning to Imagine: Integrating Counterfactual Thinking in Neural Discrete Reasoning — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  70. Least-to-most prompting enables complex reasoning in large language models — 2022
  71. MWP-BERT: Numeracy-Augmented Pre-training for Math Word Problem Solving — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
  72. Measurement Extraction with Natural Language Processing: A Review — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  73. Mintaka: A Complex, Natural, and Multilingual Dataset for End-to-End Question Answering — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  74. MixQG: Neural Question Generation with Mixed Answer Types — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
  75. Modeling Multi-hop Question Answering as Single Sequence Prediction — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  76. Models in the Loop: Aiding Crowdworkers with Generative Annotation Assistants — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  77. MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Data — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  78. MultiSpanQA: A Dataset for Multi-Span Question Answering — 2022 · Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  79. 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
  80. On the Limitations of Dataset Balancing: The Lost Battle Against Spurious Correlations — 2022 · Findings of the Association for Computational Linguistics: NAACL 2022
  81. PACIFIC: Towards Proactive Conversational Question Answering over Tabular and Textual Data in Finance — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  82. PaLM: Scaling Language Modeling with Pathways — 2022 · arXiv:2204.02311
  83. Perturbation Augmentation for Fairer NLP — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  84. 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
  85. Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks — 2022 · arXiv:2211.12588
  86. Prompt Tuning for Discriminative Pre-trained Language Models — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  87. Question Answering Infused Pre-training of General-Purpose Contextualized Representations — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  88. ROSCOE: A Suite of Metrics for Scoring Step-by-Step Reasoning — 2022 · arXiv:2212.07919
  89. Reason first, then respond: Modular Generation for Knowledge-infused Dialogue — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  90. Reasoning Like Program Executors — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  91. Reasoning with Language Model Prompting: A Survey — 2022 · arXiv:2212.09597
  92. Reframing Instructional Prompts to GPTk's Language — 2022 · Findings of the Association for Computational Linguistics: ACL 2022
  93. 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)
  94. Successive Prompting for Decomposing Complex Questions — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  95. TaCube: Pre-computing Data Cubes for Answering Numerical-Reasoning Questions over Tabular Data — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  96. Teaching Broad Reasoning Skills for Multi-Step QA by Generating Hard Contexts — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  97. To What Extent Do Natural Language Understanding Datasets Correlate to Logical Reasoning? A Method for Diagnosing Logical Reasoning. — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  98. Towards Robust Numerical Question Answering: Diagnosing Numerical Capabilities of NLP Systems — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  99. Tracing Origins: Coreference-aware Machine Reading Comprehension — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  100. Training language models to follow instructions with human feedback — 2022 · arXiv:2203.02155

Pages: 1 · 2 · 3 · 4 · 5 · 6

This page in Markdown → https://md.mova.elamur.ai/free/en/docs/papers/cited-by/dua-2019-drop-reading-comprehension-benchmark-requiring-3/