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NumNet: Machine Reading Comprehension with Numerical Reasoning

arXiv 1910.06701 ↗First posted 15 Oct 2019cs.CLcited by 59

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Abstract (arXiv)

Numerical reasoning, such as addition, subtraction, sorting and counting is a critical skill in human's reading comprehension, which has not been well considered in existing machine reading comprehension (MRC) systems. To address this issue, we propose a numerical MRC model named as NumNet, which utilizes a numerically-aware graph neural network to consider the comparing information and performs numerical reasoning over numbers in the question and passage. Our system achieves an EM-score of 64.56% on the DROP dataset, outperforming all existing machine reading comprehension models by considering the numerical relations among numbers.

Key facts. Cited by 59 papers in the map (data through 14 Oct 2026). First posted on arXiv 15 Oct 2019.

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Citing papers per year: 2021: 19; 2022: 24; 2023: 6; 2024: 5; 2025: 2; 2026: 3.

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  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  2. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,708
  3. 2021TAT-QA: A Question Answering Benchmark on a Hybrid of Tabular and Textual Content in Financecited by 408
  4. 2023REFINER: Reasoning Feedback on Intermediate Representationscited by 205
  5. 2023ChatDB: Augmenting LLMs with Databases as Their Symbolic Memorycited by 140
  6. 2021Investigating the Limitations of Transformers with Simple Arithmetic Taskscited by 139
  7. 2022MultiHiertt: Numerical Reasoning over Multi Hierarchical Tabular and Textual Datacited by 121
  8. 2022NumGLUE: A Suite of Fundamental yet Challenging Mathematical Reasoning Taskscited by 112
  9. 2021Representing Numbers in NLP: a Survey and a Visioncited by 83
  10. 2022Towards Complex Document Understanding By Discrete Reasoningcited by 82
  11. 2022Don't Blame the Annotator: Bias Already Starts in the Annotation Instructionscited by 47
  12. 2022Reasoning Like Program Executorscited by 45
38 more
  1. 2022PACIFIC: Towards Proactive Conversational Question Answering over Tabular and Textual Data in Financecited by 45
  2. 2021Turning Tables: Generating Examples from Semi-structured Tables for Endowing Language Models with Reasoning Skillscited by 39
  3. 2021DAGN: Discourse-Aware Graph Network for Logical Reasoningcited by 28
  4. 2024TAT-LLM: A Specialized Language Model for Discrete Reasoning over Tabular and Textual Datacited by 19
  5. 2021Rethinking Search: Making Domain Experts out of Dilettantescited by 18
  6. 2023Can neural networks do arithmetic? A survey on the elementary numerical skills of state-of-the-art deep learning modelscited by 18
  7. 2024Path-Consistency with Prefix Enhancement for Efficient Inference in LLMscited by 17
  8. 2021Teaching Autoregressive Language Models Complex Tasks By Demonstrationcited by 15
  9. 2021NOAHQA: Numerical Reasoning with Interpretable Graph Question Answering Datasetcited by 14
  10. 2022ELASTIC: Numerical Reasoning with Adaptive Symbolic Compilercited by 14
  11. 2022UniRPG: Unified Discrete Reasoning over Table and Text as Program Generationcited by 13
  12. 2021Towards Tractable Mathematical Reasoning: Challenges, Strategies, and Opportunities for Solving Math Word Problemscited by 12
  13. 2021NT5?! Training T5 to Perform Numerical Reasoningcited by 11
  14. 2021Weakly Supervised Neuro-Symbolic Module Networks for Numerical Reasoningcited by 10
  15. 2021Mitigating False-Negative Contexts in Multi-document Question Answering with Retrieval Marginalizationcited by 10
  16. 2021Numerical reasoning in machine reading comprehension tasks: are we there yet?cited by 9
  17. 2022A Neural-Symbolic Approach to Natural Language Understandingcited by 8
  18. 2022APOLLO: An Optimized Training Approach for Long-form Numerical Reasoningcited by 8
  19. 2022OPERA:Operation-Pivoted Discrete Reasoning over Textcited by 7
  20. 2022Reflection of Thought: Inversely Eliciting Numerical Reasoning in Language Models via Solving Linear Systemscited by 7
  21. 2022Complex Reading Comprehension Through Question Decompositioncited by 7
  22. 2022Generalizing Math Word Problem Solvers via Solution Diversificationcited by 7
  23. 2021REPT: Bridging Language Models and Machine Reading Comprehension via Retrieval-Based Pre-trainingcited by 6
  24. 2022Towards Robust Numerical Question Answering: Diagnosing Numerical Capabilities of NLP Systemscited by 6
  25. 2021Masked Measurement Prediction: Learning to Jointly Predict Quantities and Units from Textual Contextcited by 5
  26. 2023Doc2SoarGraph: Discrete Reasoning over Visually-Rich Table-Text Documents via Semantic-Oriented Hierarchical Graphscited by 5
  27. 2024How to Leverage Digit Embeddings to Represent Numbers?cited by 5
  28. 2022NAPG: Non-Autoregressive Program Generation for Hybrid Tabular-Textual Question Answeringcited by 4
  29. 2024XRAG: eXamining the Core -- Benchmarking Foundational Components in Advanced Retrieval-Augmented Generationcited by 3
  30. 2026Inclusion-of-Thoughts: Mitigating Preference Instability via Purifying the Decision Spacecited by 3
  31. 2021EviDR: Evidence-Emphasized Discrete Reasoning for Reasoning Machine Reading Comprehensioncited by 2
  32. 2021Improving Numerical Reasoning Skills in the Modular Approach for Complex Question Answering on Textcited by 2
  33. 2022Unsupervised Numerical Reasoning to Extract Phenotypes from Clinical Text by Leveraging External Knowledgecited by 2
  34. 2022Discourse-Aware Graph Networks for Textual Logical Reasoningcited by 2
  35. 2021Discrete Reasoning Templates for Natural Language Understandingcited by 1
  36. 2022Towards Differential Relational Privacy and its use in Question Answeringcited by 1
  37. 2022Teaching Neural Module Networks to Do Arithmeticcited by 1
  38. 2022How Well Do Multi-hop Reading Comprehension Models Understand Date Information?cited by 1

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