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home / docs / papers / cited-by / Who cites «Solving General Arithmetic Word Problems» · page 2

Who cites «Solving General Arithmetic Word Problems» · page 2

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

Pages: 1 · 2 · 3 · 4

  1. Re-Reading Improves Reasoning in Large Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  2. ReFT: Representation Finetuning for Language Models — 2024 · arXiv:2404.03592
  3. Reasoning in Flux: Enhancing Large Language Models Reasoning through Uncertainty-aware Adaptive Guidance — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  4. STAR: Constraint LoRA with Dynamic Active Learning for Data-Efficient Fine-Tuning of Large Language Models — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  5. SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models — 2024 · arXiv:2401.07950
  6. Self-Refine Instruction-Tuning for Aligning Reasoning in Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  7. Self-Training with Direct Preference Optimization Improves Chain-of-Thought Reasoning — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  8. Solving for X and Beyond: Can Large Language Models Solve Complex Math Problems with More-Than-Two Unknowns? — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  9. Sparse Matrix in Large Language Model Fine-tuning — 2024 · arXiv:2405.15525
  10. Symbol-LLM: Towards Foundational Symbol-centric Interface For Large Language Models — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  11. The Impact of Reasoning Step Length on Large Language Models — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  12. Towards A Unified View of Answer Calibration for Multi-Step Reasoning — 2024 · Proceedings of the 2nd Workshop on Natural Language Reasoning and Structured Explanations (@ACL 2024)
  13. TravelPlanner: A Benchmark for Real-World Planning with Language Agents — 2024 · arXiv:2402.01622
  14. Wrong-of-Thought: An Integrated Reasoning Framework with Multi-Perspective Verification and Wrong Information — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  15. Zero-Shot Chain-of-Thought Reasoning Guided by Evolutionary Algorithms in Large Language Models — 2024 · arXiv:2402.05376
  16. 面向小规模大语言模型推理优化的推理路径排序方法(A Reasoning Paths Ranking Method for Reasoning Optimization of Small-scale Large Language Models) — 2024 · Proceedings of the 23rd Chinese National Conference on Computational Linguistics (Volume 1: Main Conference)
  17. A Comprehensive Overview of Large Language Models — 2023 · arXiv:2307.06435
  18. A Survey of Deep Learning for Mathematical Reasoning — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  19. A Survey of Large Language Models — 2023 · arXiv:2303.18223 · Frontiers of Computer Science, Volume 20, Issue 12, Article 2012627 (2026)
  20. ARB: Advanced Reasoning Benchmark for Large Language Models — 2023 · arXiv:2307.13692
  21. Agent Instructs Large Language Models to be General Zero-Shot Reasoners — 2023 · arXiv:2310.03710
  22. Are Language Models Worse than Humans at Following Prompts? It's Complicated — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  23. Auto-Regressive Next-Token Predictors are Universal Learners — 2023 · arXiv:2309.06979
  24. Batch Prompting: Efficient Inference with Large Language Model APIs — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: Industry Track
  25. Better Zero-Shot Reasoning with Role-Play Prompting — 2023 · arXiv:2308.07702
  26. Better Zero-Shot Reasoning with Self-Adaptive Prompting — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  27. Chain of Thought Prompting Elicits Knowledge Augmentation — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  28. Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model Collaboration — 2023 · arXiv:2310.00280
  29. DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning — 2023 · arXiv:2310.02954
  30. Decomposed Prompting: A Modular Approach for Solving Complex Tasks — 2023 · ICLR 2023 (arXiv 2210.02406)
  31. Deductive Verification of Chain-of-Thought Reasoning — 2023 · arXiv:2306.03872
  32. Democratizing Reasoning Ability: Tailored Learning from Large Language Model — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  33. DialCoT Meets PPO: Decomposing and Exploring Reasoning Paths in Smaller Language Models — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  34. DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks — 2023 · arXiv:2309.17167
  35. Dynamic Voting for Efficient Reasoning in Large Language Models — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  36. Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate — 2023 · arXiv:2305.19118
  37. Evaluating Large Language Models: A Comprehensive Survey — 2023 · arXiv:2310.19736
  38. Exchange-of-Thought: Enhancing Large Language Model Capabilities through Cross-Model Communication — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  39. FERMAT: An Alternative to Accuracy for Numerical Reasoning — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  40. Faithful Chain-of-Thought Reasoning — 2023 · Proceedings of the 13th International Joint Conference on Natural Language Processing and the 3rd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  41. Fill in the Blank: Exploring and Enhancing LLM Capabilities for Backward Reasoning in Math Word Problems — 2023 · arXiv:2310.01991
  42. GRACE: Discriminator-Guided Chain-of-Thought Reasoning — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  43. Generalizable Chain-of-Thought Prompting in Mixed-task Scenarios with Large Language Models — 2023 · arXiv:2310.06692
  44. Getting MoRE out of Mixture of Language Model Reasoning Experts — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  45. How Many Demonstrations Do You Need for In-context Learning? — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  46. Introduction to Mathematical Language Processing: Informal Proofs, Word Problems, and Supporting Tasks — 2023
  47. Is ChatGPT a General-Purpose Natural Language Processing Task Solver? — 2023 · arXiv:2302.06476
  48. 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
  49. Language Models can Solve Computer Tasks — 2023 · arXiv:2303.17491
  50. Large Language Models are Better Reasoners with Self-Verification — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  51. Large Language Models are In-Context Semantic Reasoners rather than Symbolic Reasoners — 2023 · arXiv:2305.14825
  52. Large Language Models as Optimizers — 2023 · arXiv:2309.03409
  53. Learning to Reason and Memorize with Self-Notes — 2023 · arXiv:2305.00833
  54. 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
  55. Let''s reward step by step: Step-Level reward model as the Navigators for Reasoning — 2023 · arXiv:2310.10080
  56. 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)
  57. MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning — 2023 · arXiv:2309.05653
  58. 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)
  59. 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)
  60. Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future — 2023 · arXiv:2309.15402
  61. Plan, Verify and Switch: Integrated Reasoning with Diverse X-of-Thoughts — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  62. 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)
  63. Progressive-Hint Prompting Improves Reasoning in Large Language Models — 2023 · arXiv:2304.09797
  64. Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution — 2023 · arXiv:2309.16797
  65. 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
  66. Self-Polish: Enhance Reasoning in Large Language Models via Problem Refinement — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  67. 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)
  68. 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)
  69. Tab-CoT: Zero-shot Tabular Chain of Thought — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  70. Teaching Arithmetic to Small Transformers — 2023 · arXiv:2307.03381
  71. TheoremQA: A Theorem-driven Question Answering Dataset — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  72. Towards Reasoning in Large Language Models via Multi-Agent Peer Review Collaboration — 2023 · arXiv:2311.08152
  73. Towards Reasoning in Large Language Models: A Survey — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  74. Unleashing the potential of prompt engineering for large language models — 2023 · arXiv:2310.14735 · Patterns 6(6) 101260 (2025)
  75. WizardMath: Empowering Mathematical Reasoning for Large Language Models via Reinforced Evol-Instruct — 2023 · arXiv:2308.09583
  76. World Models for Math Story Problems — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  77. AlexaTM 20B: Few-Shot Learning Using a Large-Scale Multilingual Seq2Seq Model — 2022 · arXiv:2208.01448
  78. 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
  79. Automatic Chain of Thought Prompting in Large Language Models — 2022 · arXiv:2210.03493
  80. Chain-of-Thought Prompting Elicits Reasoning in Large Language Models — 2022 · arXiv:2201.11903
  81. Complexity-Based Prompting for Multi-Step Reasoning — 2022 · arXiv:2210.00720
  82. HAWP: a Dataset for Hindi Arithmetic Word Problem Solving — 2022 · Proceedings of the Thirteenth Language Resources and Evaluation Conference
  83. Investigating Math Word Problems using Pretrained Multilingual Language Models — 2022 · Proceedings of the 1st Workshop on Mathematical Natural Language Processing (MathNLP)
  84. LILA: A Unified Benchmark for Mathematical Reasoning — 2022 · Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing
  85. Large Language Models Are Human-Level Prompt Engineers — 2022 · arXiv:2211.01910
  86. Large language models are zero-shot reasoners — 2022
  87. 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)
  88. Mind''s Eye: Grounded Language Model Reasoning through Simulation — 2022 · arXiv:2210.05359
  89. 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)
  90. Program of Thoughts Prompting: Disentangling Computation from Reasoning for Numerical Reasoning Tasks — 2022 · arXiv:2211.12588
  91. Reasoning with Language Model Prompting: A Survey — 2022 · arXiv:2212.09597
  92. Self-Consistency Improves Chain of Thought Reasoning in Language Models — 2022 · arXiv:2203.11171
  93. Why are NLP Models Fumbling at Elementary Math? A Survey of Deep Learning based Word Problem Solvers — 2022 · arXiv 2205.15683
  94. A Bottom-Up DAG Structure Extraction Model for Math Word Problems — 2021 · AAAI 2021
  95. Generate & Rank: A Multi-task Framework for Math Word Problems — 2021 · Findings of the Association for Computational Linguistics: EMNLP 2021
  96. Improving Math Word Problems with Pre-trained Knowledge and Hierarchical Reasoning — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  97. Mapping probability word problems to executable representations — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  98. Math Word Problem Generation with Mathematical Consistency and Problem Context Constraints — 2021 · Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
  99. 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)
  100. NaturalProofs: Mathematical Theorem Proving in Natural Language — 2021 · arXiv:2104.01112

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