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Who cites «Solving General Arithmetic Word Problems» · page 3

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

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  1. Fill in the Blank: Exploring and Enhancing LLM Capabilities for Backward Reasoning in Math Word Problems — 2023 · arXiv:2310.01991
  2. GRACE: Discriminator-Guided Chain-of-Thought Reasoning — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  3. Generalizable Chain-of-Thought Prompting in Mixed-task Scenarios with Large Language Models — 2023 · arXiv:2310.06692
  4. Getting MoRE out of Mixture of Language Model Reasoning Experts — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  5. How Many Demonstrations Do You Need for In-context Learning? — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  6. Introduction to Mathematical Language Processing: Informal Proofs, Word Problems, and Supporting Tasks — 2023
  7. Is ChatGPT a General-Purpose Natural Language Processing Task Solver? — 2023 · arXiv:2302.06476
  8. LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  9. Language Models can Solve Computer Tasks — 2023 · arXiv:2303.17491
  10. Large Language Models are Better Reasoners with Self-Verification — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  11. Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners — 2023 · arXiv:2305.14825
  12. Large Language Models as Optimizers — 2023 · arXiv:2309.03409
  13. Learning to Reason and Memorize with Self-Notes — 2023 · arXiv:2305.00833
  14. Let GPT be a Math Tutor: Teaching Math Word Problem Solvers with Customized Exercise Generation — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  15. Let''s reward step by step: Step-Level reward model as the Navigators for Reasoning — 2023 · arXiv:2310.10080
  16. Limitations of Language Models in Arithmetic and Symbolic Induction — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  17. MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning — 2023 · arXiv:2309.05653
  18. 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)
  19. Math Word Problem Solving by Generating Linguistic Variants of Problem Statements — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 4: Student Research Workshop)
  20. Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future — 2023 · arXiv:2309.15402
  21. Plan, Verify and Switch: Integrated Reasoning with Diverse X-of-Thoughts — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  22. Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Models — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  23. Progressive-Hint Prompting Improves Reasoning in Large Language Models — 2023 · arXiv:2304.09797
  24. Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution — 2023 · arXiv:2309.16797
  25. R$^3$ Prompting: Review, Rephrase and Resolve for Chain-of-Thought Reasoning in Large Language Models under Noisy Context — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  26. Self-Polish: Enhance Reasoning in Large Language Models via Problem Refinement — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  27. Solving Math Word Problems via Cooperative Reasoning induced Language Models — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  28. Symbolic Chain-of-Thought Distillation: Small Models Can Also ``Think'''' Step-by-Step — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  29. Tab-CoT: Zero-shot Tabular Chain of Thought — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  30. Teaching Arithmetic to Small Transformers — 2023 · arXiv:2307.03381
  31. TheoremQA: A Theorem-driven Question Answering Dataset — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  32. Towards Reasoning in Large Language Models via Multi-Agent Peer Review Collaboration — 2023 · arXiv:2311.08152
  33. Towards Reasoning in Large Language Models: A Survey — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  34. Unleashing the potential of prompt engineering for large language models — 2023 · arXiv:2310.14735 · Patterns 6(6) 101260 (2025)
  35. WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct — 2023 · arXiv:2308.09583
  36. World Models for Math Story Problems — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  37. AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model — 2022 · arXiv:2208.01448
  38. Augmenting Operations Research with Auto-Formulation of Optimization Models From Problem Descriptions — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing: Industry Track
  39. Automatic Chain of Thought Prompting in Large Language Models — 2022 · arXiv:2210.03493
  40. Chain-of-Thought Prompting Elicits Reasoning in Large Language Models — 2022 · arXiv:2201.11903
  41. Complexity-Based Prompting for Multi-Step Reasoning — 2022 · arXiv:2210.00720
  42. EPT-X: An Expression-Pointer Transformer model that generates eXplanations for numbers — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  43. HAWP: a Dataset for Hindi Arithmetic Word Problem Solving — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
  44. Investigating Math Word Problems using Pretrained Multilingual Language Models — 2022 · Proceedings of the 1st Workshop on Mathematical Natural Language Processing (MathNLP)
  45. LILA: A Unified Benchmark for Mathematical Reasoning — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  46. Large Language Models Are Human-Level Prompt Engineers — 2022 · arXiv:2211.01910
  47. Large language models are zero-shot reasoners — 2022
  48. Learning to Reason Deductively: Math Word Problem Solving as Complex Relation Extraction — our card · 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  49. Mind''s Eye: Grounded Language Model Reasoning through Simulation — 2022 · arXiv:2210.05359
  50. Noun-MWP: Math Word Problems Meet Noun Answers — 2022 · Proceedings of the 29th International Conference on Computational Linguistics
  51. NumGLUE: A Suite of Fundamental yet Challenging Mathematical Reasoning Tasks — 2022 · Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  52. Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks — 2022 · arXiv:2211.12588
  53. Reasoning with Language Model Prompting: A Survey — 2022 · arXiv:2212.09597
  54. Self-Consistency Improves Chain of Thought Reasoning in Language Models — 2022 · arXiv:2203.11171
  55. Textual Enhanced Contrastive Learning for Solving Math Word Problems — 2022 · Findings of the Association for Computational Linguistics: EMNLP 2022
  56. Why are NLP Models Fumbling at Elementary Math? A Survey of Deep Learning based Word Problem Solvers — 2022 · arXiv 2205.15683
  57. A Bottom-Up DAG Structure Extraction Model for Math Word Problems — 2021 · AAAI 2021
  58. Generate & Rank: A Multi-task Framework for Math Word Problems — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
  59. Improving Math Word Problems with Pre-trained Knowledge and Hierarchical Reasoning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  60. Mapping probability word problems to executable representations — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  61. Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  62. Math Word Problem Solving with Explicit Numerical Values — 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)
  63. NaturalProofs: Mathematical Theorem Proving in Natural Language — 2021 · arXiv:2104.01112
  64. Neural-Symbolic Solver for Math Word Problems with Auxiliary Tasks — 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)
  65. Representing Numbers in NLP: a Survey and a Vision — 2021 · Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
  66. Training Verifiers to Solve Math Word Problems — 2021 · arXiv:2110.14168
  67. A Diverse Corpus for Evaluating and Developing English Math Word Problem Solvers — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  68. A Knowledge-Aware Sequence-to-Tree Network for Math Word Problem Solving — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  69. An Empirical Investigation of Contextualized Number Prediction — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  70. Graph-to-Tree Learning for Solving Math Word Problems — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  71. Injecting Numerical Reasoning Skills into Language Models — 2020 · Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics
  72. Point to the Expression: Solving Algebraic Word Problems using the Expression-Pointer Transformer Model — 2020 · Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP)
  73. Recurrent Inference in Text Editing — 2020 · Findings of the Association for Computational Linguistics: EMNLP 2020
  74. Solving Arithmetic Word Problems Using Transformer and Pre-processing of Problem Texts — 2020 · Proceedings of the 17th International Conference on Natural Language Processing (ICON)
  75. Giving BERT a Calculator: Finding Operations and Arguments with Reading Comprehension — 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)
  76. Modeling Intra-Relation in Math Word Problems with Different Functional Multi-Head Attentions — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
  77. 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)
  78. ProblemSolver at SemEval-2019 Task 10: Sequence-to-Sequence Learning and Expression Trees — 2019 · Proceedings of the 13th International Workshop on Semantic Evaluation
  79. Quantity Tagger: A Latent-Variable Sequence Labeling Approach to Solving Addition-Subtraction Word Problems — 2019 · Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
  80. SemEval-2019 Task 10: Math Question Answering — 2019 · Proceedings of the 13th International Workshop on Semantic Evaluation
  81. Semantically-Aligned Equation Generation for Solving and Reasoning Math Word Problems — 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)
  82. Template-Based Math Word Problem Solvers with Recursive Neural Networks — 2019 · AAAI 2019
  83. Text2Math: End-to-end Parsing Text into Math Expressions — 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)
  84. The Gap of Semantic Parsing: A Survey on Automatic Math Word Problem Solvers — 2019 · IEEE TPAMI 42(9), 2020 (arXiv 1808.07290)
  85. Tree-structured Decoding for Solving Math Word Problems — 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)
  86. Where's My Head? Definition, Data Set, and Models for Numeric Fused-Head Identification and Resolution — 2019 · Transactions of the Association for Computational Linguistics
  87. A Meaning-Based Statistical English Math Word Problem Solver — 2018 · Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)
  88. Data-Driven Methods for Solving Algebra Word Problems — 2018 · arXiv 1804.10718
  89. DeepProbLog: Neural Probabilistic Logic Programming — 2018 · arXiv:1805.10872
  90. EquGener: A Reasoning Network for Word Problem Solving by Generating Arithmetic Equations — 2018 · Proceedings of the 32nd Pacific Asia Conference on Language, Information and Computation
  91. Mapping to Declarative Knowledge for Word Problem Solving — our card · 2018
  92. MathDQN: Solving Arithmetic Word Problems via Deep Reinforcement Learning — 2018 · AAAI 2018
  93. Neural Math Word Problem Solver with Reinforcement Learning — 2018 · Proceedings of the 27th International Conference on Computational Linguistics
  94. Numeracy for Language Models: Evaluating and Improving their Ability to Predict Numbers — 2018 · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  95. Translating a Math Word Problem to a Expression Tree — 2018 · Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing
  96. Translating a Math Word Problem to an Expression Tree — 2018 · arXiv:1811.05632
  97. Using Intermediate Representations to Solve Math Word Problems — 2018 · Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  98. Annotating Derivations: A New Evaluation Strategy and Dataset for Algebra Word Problems — 2017 · Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, Long Papers
  99. Beyond Sentential Semantic Parsing: Tackling the Math SAT with a Cascade of Tree Transducers — 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
  100. Deep Neural Solver for Math Word Problems — 2017 · Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing

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