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Who cites «Are NLP Models really able to Solve Simple Math Word Problems?» · page 5

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

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  1. SAAS: Solving Ability Amplification Strategy for Enhanced Mathematical Reasoning in Large Language Models — 2024 · arXiv:2404.03887
  2. SIBO: A Simple Booster for Parameter-Efficient Fine-Tuning — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  3. SIaM: Self-Improving Code-Assisted Mathematical Reasoning of Large Language Models — 2024 · arXiv:2408.15565
  4. SQFT: Low-cost Model Adaptation in Low-precision Sparse Foundation Models — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  5. SceMQA: A Scientific College Entrance Level Multimodal Question Answering Benchmark — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
  6. SciCode: A Research Coding Benchmark Curated by Scientists — 2024 · arXiv:2407.13168
  7. SciInstruct: a Self-Reflective Instruction Annotated Dataset for Training Scientific Language Models — 2024 · arXiv:2401.07950
  8. Self-Consistency Boosts Calibration for Math Reasoning — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  9. Self-Contrast: Better Reflection Through Inconsistent Solving Perspectives — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  10. Self-Para-Consistency: Improving Reasoning Tasks at Low Cost for Large Language Models — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  11. 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)
  12. Self-training Language Models for Arithmetic Reasoning — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  13. SemEval-2024 Task 2: Safe Biomedical Natural Language Inference for Clinical Trials — 2024 · Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
  14. Shears: Unstructured Sparsity with Neural Low-rank Adapter Search — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 6: Industry Track)
  15. Solving General Natural-Language-Description Optimization Problems with Large Language Models — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 6: Industry Track)
  16. 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
  17. Sparse Matrix in Large Language Model Fine-tuning — 2024 · arXiv:2405.15525
  18. Speculative Knowledge Distillation: Bridging the Teacher-Student Gap Through Interleaved Sampling — 2024 · arXiv:2410.11325
  19. SportsMetrics: Blending Text and Numerical Data to Understand Information Fusion in LLMs — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  20. Subjective Topic meets LLMs: Unleashing Comprehensive, Reflective and Creative Thinking through the Negation of Negation — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  21. 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)
  22. Task Oriented In-Domain Data Augmentation — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  23. Teaching Large Language Models to Reason with Reinforcement Learning — 2024 · arXiv:2403.04642
  24. Teaching Small Language Models Reasoning through Counterfactual Distillation — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  25. The Impact of Reasoning Step Length on Large Language Models — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  26. ToolRerank: Adaptive and Hierarchy-Aware Reranking for Tool Retrieval — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  27. Toolink: Linking Toolkit Creation and Using through Chain-of-Solving on Open-Source Model — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  28. Toward Adaptive Reasoning in Large Language Models with Thought Rollback — 2024 · arXiv:2412.19707
  29. 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)
  30. Towards Human-aligned Evaluation for Linear Programming Word Problems — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  31. TravelPlanner: A Benchmark for Real-World Planning with Language Agents — 2024 · arXiv:2402.01622
  32. Trustworthiness and Self-awareness in Large Language Models: An Exploration through the Think-Solve-Verify Framework — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  33. What Makes Math Word Problems Challenging for LLMs? — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
  34. When Reasoning Meets Information Aggregation: A Case Study with Sports Narratives — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  35. Wrong-of-Thought: An Integrated Reasoning Framework with Multi-Perspective Verification and Wrong Information — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  36. Zero-Shot Chain-of-Thought Reasoning Guided by Evolutionary Algorithms in Large Language Models — 2024 · arXiv:2402.05376
  37. mCoT: Multilingual Instruction Tuning for Reasoning Consistency in Language Models — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  38. 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)
  39. A Categorical Archive of ChatGPT Failures — 2023 · arXiv:2302.03494
  40. A Causal Framework to Quantify the Robustness of Mathematical Reasoning with Language Models — 2023 · Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  41. A Comprehensive Overview of Large Language Models — 2023 · arXiv:2307.06435
  42. A Generation-based Deductive Method for Math Word Problems — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  43. A Human-on-the-Loop Optimization Autoformalism Approach for Sustainability — 2023 · arXiv:2308.10380
  44. A Real-World WebAgent with Planning, Long Context Understanding, and Program Synthesis — 2023 · arXiv:2307.12856
  45. A Survey of Large Language Models — 2023 · arXiv:2303.18223 · Frontiers of Computer Science, Volume 20, Issue 12, Article 2012627 (2026)
  46. ARB: Advanced Reasoning Benchmark for Large Language Models — 2023 · arXiv:2307.13692
  47. ART: Automatic multi-step reasoning and tool-use for large language models — 2023 · arXiv:2303.09014
  48. ATHENA: Mathematical Reasoning with Thought Expansion — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  49. Active Prompting with Chain-of-Thought for Large Language Models — 2023 · arXiv:2302.12246
  50. Agent Instructs Large Language Models to be General Zero-Shot Reasoners — 2023 · arXiv:2310.03710
  51. Agent Lumos: Unified and Modular Training for Open-Source Language Agents — 2023 · arXiv:2311.05657
  52. An Expression Tree Decoding Strategy for Mathematical Equation Generation — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  53. Analyzing ChatGPT''s Mathematical Deficiencies: Insights and Contributions — 2023 · Proceedings of the 35th Conference on Computational Linguistics and Speech Processing (ROCLING 2023)
  54. Automatic Model Selection with Large Language Models for Reasoning — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  55. Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  56. Batch Prompting: Efficient Inference with Large Language Model APIs — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing: Industry Track
  57. Benchmarks for Automated Commonsense Reasoning: A Survey — 2023 · arXiv:2302.04752
  58. Better Zero-Shot Reasoning with Role-Play Prompting — 2023 · arXiv:2308.07702
  59. Bridging the Resource Gap: Exploring the Efficacy of English and Multilingual LLMs for Swedish — 2023 · Proceedings of the Second Workshop on Resources and Representations for Under-Resourced Languages and Domains (RESOURCEFUL-2023)
  60. CREATOR: Tool Creation for Disentangling Abstract and Concrete Reasoning of Large Language Models — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  61. CRITIC: Large Language Models Can Self-Correct with Tool-Interactive Critiquing — 2023 · arXiv:2305.11738
  62. Calc-X and Calcformers: Empowering Arithmetical Chain-of-Thought through Interaction with Symbolic Systems — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  63. Can LLMs Express Their Uncertainty? An Empirical Evaluation of Confidence Elicitation in LLMs — 2023 · arXiv:2306.13063
  64. Can Language Models Solve Graph Problems in Natural Language? — 2023 · arXiv:2305.10037
  65. Chain of Thought Prompting Elicits Knowledge Augmentation — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  66. Chameleon: Plug-and-Play Compositional Reasoning with Large Language Models — 2023 · arXiv:2304.09842
  67. Conic10K: A Challenging Math Problem Understanding and Reasoning Dataset — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  68. Contrastive Chain-of-Thought Prompting — 2023 · arXiv:2311.09277
  69. Contrastive Decoding Improves Reasoning in Large Language Models — 2023 · arXiv:2309.09117
  70. Corex: Pushing the Boundaries of Complex Reasoning through Multi-Model Collaboration — 2023 · arXiv:2310.00280
  71. DQ-LoRe: Dual Queries with Low Rank Approximation Re-ranking for In-Context Learning — 2023 · arXiv:2310.02954
  72. Defining a New NLP Playground — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  73. Democratizing Reasoning Ability: Tailored Learning from Large Language Model — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  74. Design of Chain-of-Thought in Math Problem Solving — 2023 · arXiv:2309.11054
  75. 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
  76. Distilling Reasoning Capabilities into Smaller Language Models — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  77. Distilling Step-by-Step! Outperforming Larger Language Models with Less Training Data and Smaller Model Sizes — 2023 · Findings of the Association for Computational Linguistics: ACL 2023
  78. Don''t be Blind to Questions: Question-Oriented Math Word Problem Solving — 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)
  79. DyVal: Dynamic Evaluation of Large Language Models for Reasoning Tasks — 2023 · arXiv:2309.17167
  80. Dynamic Voting for Efficient Reasoning in Large Language Models — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  81. Evaluating Large Language Models: A Comprehensive Survey — 2023 · arXiv:2310.19736
  82. 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
  83. Explaining Math Word Problem Solvers — 2023 · arXiv:2307.13128 · Published in 6th International Conference on Natural Language Processing and Information Retrieval (NLPIR 2022)
  84. Explanation Selection Using Unlabeled Data for Chain-of-Thought Prompting — 2023 · Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing
  85. Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular Data — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  86. Expression Syntax Information Bottleneck for Math Word Problems — 2023 · arXiv:2310.15664
  87. 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)
  88. 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)
  89. Fill in the Blank: Exploring and Enhancing LLM Capabilities for Backward Reasoning in Math Word Problems — 2023 · arXiv:2310.01991
  90. Foundation Models for Decision Making: Problems, Methods, and Opportunities — 2023 · arXiv:2303.04129
  91. From Zero to Hero: Examining the Power of Symbolic Tasks in Instruction Tuning — 2023 · arXiv:2304.07995
  92. Frugal LMs Trained to Invoke Symbolic Solvers Achieve Parameter-Efficient Arithmetic Reasoning — 2023 · arXiv:2312.05571
  93. GRACE: Discriminator-Guided Chain-of-Thought Reasoning — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  94. Generalizable Chain-of-Thought Prompting in Mixed-task Scenarios with Large Language Models — 2023 · arXiv:2310.06692
  95. Getting MoRE out of Mixture of Language Model Reasoning Experts — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  96. Graph-ToolFormer: To Empower LLMs with Graph Reasoning Ability via Prompt Augmented by ChatGPT — 2023 · arXiv:2304.11116
  97. GraphReason: Enhancing Reasoning Capabilities of Large Language Models through A Graph-Based Verification Approach — 2023 · arXiv:2308.09267
  98. Harnessing the Power of LLMs in Practice: A Survey on ChatGPT and Beyond — 2023 · arXiv:2304.13712
  99. How Many Demonstrations Do You Need for In-context Learning? — 2023 · Findings of the Association for Computational Linguistics: EMNLP 2023
  100. Improving Mathematics Tutoring With A Code Scratchpad — 2023 · Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023)

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