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Who cites «Learning to Solve Arithmetic Word Problems with Verb Categorization»

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

Pages: 1 · 2 · 3

  1. FormulaReasoning: A Dataset for Formula-Based Numerical Reasoning — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
  2. G-LoRA: Global-Local Decoupled Low-Rank Adaptation — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
  3. GRASS: Gradient-based Adaptive Layer-wise Importance Sampling for Memory-efficient Large Language Model Fine-tuning — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
  4. Localized Low-Rank Adaptation within Clustered Parameter Subspaces — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  5. TARE: Lightweight Token-Aware Representation Editing for Fine-tuning Transformer-like Models — 2026 · Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  6. TabularMath: Understanding Math Reasoning over Tables with Large Language Models — 2026 · Findings of the Association for Computational Linguistics: ACL 2026
  7. A Survey on Feedback-based Multi-step Reasoning for Large Language Models on Mathematics — 2025 · arXiv:2502.14333
  8. A Systematic Survey of Automatic Prompt Optimization Techniques — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  9. Advancing Collaborative Debates with Role Differentiation through Multi-Agent Reinforcement Learning — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  10. BanglaMATH : A Bangla benchmark dataset for testing LLM mathematical reasoning at grades 6, 7, and 8 — 2025 · Proceedings of The 3rd Workshop on Mathematical Natural Language Processing (MathNLP 2025)
  11. Chain-of-Reasoning: Towards Unified Mathematical Reasoning in Large Language Models via a Multi-Paradigm Perspective — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  12. DenseLoRA: Dense Low-Rank Adaptation of Large Language Models — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  13. Error Classification of Large Language Models on Math Word Problems: A Dynamically Adaptive Framework — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
  14. Evaluating LLMs with Multiple Problems at once — 2025 · Proceedings of the Fourth Workshop on Generation, Evaluation and Metrics (GEM\texttwosuperior)
  15. Evaluating Numeracy of Language Models as a Natural Language Inference Task — 2025 · Findings of the Association for Computational Linguistics: NAACL 2025
  16. Full-Step-DPO: Self-Supervised Preference Optimization with Step-wise Rewards for Mathematical Reasoning — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  17. Generating Pedagogically Meaningful Visuals for Math Word Problems: A New Benchmark and Analysis of Text-to-Image Models — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  18. Implicit Reasoning in Large Language Models: A Comprehensive Survey — 2025 · arXiv:2509.02350
  19. Learning Text Styles: A Study on Transfer, Attribution, and Verification — 2025 · arXiv:2507.16530
  20. Make Every Penny Count: Difficulty-Adaptive Self-Consistency for Cost-Efficient Reasoning — 2025 · Findings of the Association for Computational Linguistics: NAACL 2025
  21. On the Generalization vs Fidelity Paradox in Knowledge Distillation — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  22. Persona is a Double-Edged Sword: Rethinking the Impact of Role-play Prompts in Zero-shot Reasoning Tasks — 2025 · Proceedings of the 14th International Joint Conference on Natural Language Processing and the 4th Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics
  23. Principled Personas: Defining and Measuring the Intended Effects of Persona Prompting on Task Performance — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  24. Propulsion: Steering LLM with Tiny Fine-Tuning — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
  25. RoCoFT: Efficient Finetuning of Large Language Models with Row-Column Updates — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  26. Self-Harmonized Chain of Thought — 2025 · Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  27. Skip-Thinking: Chunk-wise Chain-of-Thought Distillation Enable Smaller Language Models to Reason Better and Faster — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  28. Towards Efficient CoT Distillation: Self-Guided Rationale Selector for Better Performance with Fewer Rationales — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
  29. Towards Large Reasoning Models: A Survey of Reinforced Reasoning with Large Language Models — 2025 · arXiv:2501.09686
  30. UBench: Benchmarking Uncertainty in Large Language Models with Multiple Choice Questions — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  31. UORA: Uniform Orthogonal Reinitialization Adaptation in Parameter Efficient Fine-Tuning of Large Models — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  32. VCSearch: Bridging the Gap Between Well-Defined and Ill-Defined Problems in Mathematical Reasoning — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  33. Adaption-of-Thought: Learning Question Difficulty Improves Large Language Models for Reasoning — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  34. Aggregation of Reasoning: A Hierarchical Framework for Enhancing Answer Selection in Large Language Models — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  35. Bridging the Gap between Different Vocabularies for LLM Ensemble — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  36. ConceptMath: A Bilingual Concept-wise Benchmark for Measuring Mathematical Reasoning of Large Language Models — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  37. DocMath-Eval: Evaluating Math Reasoning Capabilities of LLMs in Understanding Long and Specialized Documents — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  38. Enhancing Chain-of-Thoughts Prompting with Iterative Bootstrapping in Large Language Models — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
  39. Escape Sky-high Cost: Early-stopping Self-Consistency for Multi-step Reasoning — 2024 · arXiv:2401.10480
  40. Explicit Memory Learning with Expectation Maximization — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  41. Exploring Reversal Mathematical Reasoning Ability for Large Language Models — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  42. Fewer is More: Boosting Math Reasoning with Reinforced Context Pruning — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  43. Forward-Backward Reasoning in Large Language Models for Mathematical Verification — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  44. Improving Language Model Reasoning with Self-motivated Learning — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  45. Instructing Large Language Models to Identify and Ignore Irrelevant Conditions — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  46. Interpreting and Improving Large Language Models in Arithmetic Calculation — 2024 · arXiv:2409.01659
  47. Large Language Models for Mathematical Reasoning: Progresses and Challenges — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: Student Research Workshop
  48. LoNAS: Elastic Low-Rank Adapters for Efficient Large Language Models — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  49. Making Language Models Better Tool Learners with Execution Feedback — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  50. Meta-Reasoning: Semantics-Symbol Deconstruction for Large Language Models — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  51. Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving — 2024 · arXiv:2405.12205
  52. MinT: Boosting Generalization in Mathematical Reasoning via Multi-view Fine-tuning — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  53. NUMCoT: Numerals and Units of Measurement in Chain-of-Thought Reasoning using Large Language Models — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  54. Orca-Math: Unlocking the potential of SLMs in Grade School Math — 2024 · arXiv:2402.14830
  55. Personality Alignment of Large Language Models — 2024 · arXiv:2408.11779
  56. Prompt Space Optimizing Few-shot Reasoning Success with Large Language Models — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
  57. RankPrompt: Step-by-Step Comparisons Make Language Models Better Reasoners — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  58. Re-Reading Improves Reasoning in Large Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  59. ReFT: Representation Finetuning for Language Models — 2024 · arXiv:2404.03592
  60. 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)
  61. SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models — 2024 · arXiv:2401.07950
  62. 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
  63. Sparse Matrix in Large Language Model Fine-tuning — 2024 · arXiv:2405.15525
  64. 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)
  65. Wrong-of-Thought: An Integrated Reasoning Framework with Multi-Perspective Verification and Wrong Information — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  66. Zero-Shot Chain-of-Thought Reasoning Guided by Evolutionary Algorithms in Large Language Models — 2024 · arXiv:2402.05376
  67. 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)
  68. Batch Prompting: Efficient Inference with Large Language Model APIs — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: Industry Track
  69. Better Zero-Shot Reasoning with Role-Play Prompting — 2023 · arXiv:2308.07702
  70. Better Zero-Shot Reasoning with Self-Adaptive Prompting — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  71. Chain of Thought Prompting Elicits Knowledge Augmentation — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  72. Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model Collaboration — 2023 · arXiv:2310.00280
  73. Deductive Verification of Chain-of-Thought Reasoning — 2023 · arXiv:2306.03872
  74. Defining a New NLP Playground — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  75. Distilling Reasoning Capabilities into Smaller Language Models — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  76. Encouraging Divergent Thinking in Large Language Models through Multi-Agent Debate — 2023 · arXiv:2305.19118
  77. Evaluating Large Language Models: A Comprehensive Survey — 2023 · arXiv:2310.19736
  78. 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
  79. Generalizable Chain-of-Thought Prompting in Mixed-task Scenarios with Large Language Models — 2023 · arXiv:2310.06692
  80. How Many Demonstrations Do You Need for In-context Learning? — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  81. Intégration du raisonnement numérique dans les modèles de langue : État de l''art et direction de recherche — 2023 · Actes de CORIA-TALN 2023. Actes de la 18e Conférence en Recherche d'Information et Applications (CORIA)
  82. Is ChatGPT a General-Purpose Natural Language Processing Task Solver? — 2023 · arXiv:2302.06476
  83. It Ain''t Over: A Multi-aspect Diverse Math Word Problem Dataset — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  84. 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
  85. Language Models can Solve Computer Tasks — 2023 · arXiv:2303.17491
  86. Large Language Models are Better Reasoners with Self-Verification — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  87. 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
  88. Let''s reward step by step: Step-Level reward model as the Navigators for Reasoning — 2023 · arXiv:2310.10080
  89. MAmmoTH: Building Math Generalist Models through Hybrid Instruction Tuning — 2023 · arXiv:2309.05653
  90. 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)
  91. Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future — 2023 · arXiv:2309.15402
  92. Orca 2: Teaching Small Language Models How to Reason — 2023 · arXiv:2311.11045
  93. Plan, Verify and Switch: Integrated Reasoning with Diverse X-of-Thoughts — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  94. 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)
  95. Progressive-Hint Prompting Improves Reasoning in Large Language Models — 2023 · arXiv:2304.09797
  96. Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution — 2023 · arXiv:2309.16797
  97. 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
  98. Tab-CoT: Zero-shot Tabular Chain of Thought — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  99. TheoremQA: A Theorem-driven Question Answering Dataset — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  100. Through the Lens of Core Competency: Survey on Evaluation of Large Language Models — 2023 · arXiv:2308.07902

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