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

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  1. Enhancing Arguments Recognition for Financial Mathematical Reasoning over Hybrid Data — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  2. Enhancing Chain-of-Thoughts Prompting with Iterative Bootstrapping in Large Language Models — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
  3. Enhancing Language Model Rationality with Bi-Directional Deliberation Reasoning — 2024 · arXiv:2407.06112
  4. Escape Sky-high Cost: Early-stopping Self-Consistency for Multi-step Reasoning — 2024 · arXiv:2401.10480
  5. Evaluating LLMs' Mathematical Reasoning in Financial Document Question Answering — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  6. Evaluating Mathematical Reasoning of Large Language Models: A Focus on Error Identification and Correction — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  7. Evolutionary Pre-Prompt Optimization for Mathematical Reasoning — 2024 · arXiv:2412.04291
  8. Explanation-aware Soft Ensemble Empowers Large Language Model In-context Learning — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  9. Explicit Memory Learning with Expectation Maximization — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  10. Exploring Reversal Mathematical Reasoning Ability for Large Language Models — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  11. Exploring the Compositional Deficiency of Large Language Models in Mathematical Reasoning Through Trap Problems — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  12. Fewer is More: Boosting Math Reasoning with Reinforced Context Pruning — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  13. FinanceMATH: Knowledge-Intensive Math Reasoning in Finance Domains — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  14. Forward-Backward Reasoning in Large Language Models for Mathematical Verification — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  15. From Bottom to Top: Extending the Potential of Parameter Efficient Fine-Tuning — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  16. From Good to Great: Improving Math Reasoning with Tool-Augmented Interleaf Prompting — 2024 · Proceedings of the 2nd Workshop on Natural Language Reasoning and Structured Explanations (@ACL 2024)
  17. GEAR: Augmenting Language Models with Generalizable and Efficient Tool Resolution — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  18. GLaPE: Gold Label-agnostic Prompt Evaluation for Large Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  19. GLoRe: When, Where, and How to Improve LLM Reasoning via Global and Local Refinements — 2024 · arXiv:2402.10963
  20. GOLD: Generalized Knowledge Distillation via Out-of-Distribution-Guided Language Data Generation — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
  21. GSM-Plus: A Comprehensive Benchmark for Evaluating the Robustness of LLMs as Mathematical Problem Solvers — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  22. Give me a hint: Can LLMs take a hint to solve math problems? — 2024 · arXiv:2410.05915
  23. Harnessing the Power of Multiple Minds: Lessons Learned from LLM Routing — 2024 · Proceedings of the Fifth Workshop on Insights from Negative Results in NLP
  24. Has It All Been Solved? Open NLP Research Questions Not Solved by Large Language Models — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  25. How Do Humans Write Code? Large Models Do It the Same Way Too — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  26. How to Train Data-Efficient LLMs — 2024 · arXiv:2402.09668
  27. 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)
  28. Improving Large Language Models via Fine-grained Reinforcement Learning with Minimum Editing Constraint — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  29. 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)
  30. Interpreting and Improving Large Language Models in Arithmetic Calculation — 2024 · arXiv:2409.01659
  31. Is C4 Dataset Optimal for Pruning? An Investigation of Calibration Data for LLM Pruning — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  32. JiuZhang3.0: Efficiently Improving Mathematical Reasoning by Training Small Data Synthesis Models — 2024 · arXiv:2405.14365
  33. Just Ask One More Time! Self-Agreement Improves Reasoning of Language Models in (Almost) All Scenarios — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  34. Key-Point-Driven Data Synthesis with its Enhancement on Mathematical Reasoning — 2024 · arXiv:2403.02333
  35. Knowing What LLMs DO NOT Know: A Simple Yet Effective Self-Detection Method — 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. L2CEval: Evaluating Language-to-Code Generation Capabilities of Large Language Models — 2024 · Transactions of the Association for Computational Linguistics
  37. LLM Reasoning Engine: Specialized Training for Enhanced Mathematical Reasoning — 2024 · arXiv:2412.20227
  38. LangBridge: Multilingual Reasoning Without Multilingual Supervision — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  39. 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
  40. Latent Learningscape Guided In-context Learning — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  41. Layer-wise Importance Matters: Less Memory for Better Performance in Parameter-efficient Fine-tuning of Large Language Models — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  42. Learn Beyond The Answer: Training Language Models with Reflection for Mathematical Reasoning — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  43. Learning to Maximize Mutual Information for Chain-of-Thought Distillation — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  44. Learning to Paraphrase for Alignment with LLM Preference — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  45. Leveraging Web-Crawled Data for High-Quality Fine-Tuning — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  46. 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)
  47. LogicAsker: Evaluating and Improving the Logical Reasoning Ability of Large Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  48. LogicBench: Towards Systematic Evaluation of Logical Reasoning Ability of Large Language Models — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  49. MAPO: Advancing Multilingual Reasoning through Multilingual-Alignment-as-Preference Optimization — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  50. MATHWELL: Generating Educational Math Word Problems Using Teacher Annotations — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  51. MIDGARD: Self-Consistency Using Minimum Description Length for Structured Commonsense Reasoning — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  52. MLCopilot: Unleashing the Power of Large Language Models in Solving Machine Learning Tasks — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  53. 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)
  54. Making Large Language Models Better Reasoners with Orchestrated Streaming Experiences — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  55. Math Problem Solving: Enhancing Large Language Models with Semantically Rich Symbolic Variables — 2024 · Proceedings of the 2nd Workshop on Mathematical Natural Language Processing @ LREC-COLING 2024
  56. MathChat: Benchmarking Mathematical Reasoning and Instruction Following in Multi-Turn Interactions — 2024 · arXiv:2405.19444
  57. MathFish: Evaluating Language Model Math Reasoning via Grounding in Educational Curricula — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  58. MathGenie: Generating Synthetic Data with Question Back-translation for Enhancing Mathematical Reasoning of LLMs — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  59. Mentor-KD: Making Small Language Models Better Multi-step Reasoners — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  60. Metacognitive Capabilities of LLMs: An Exploration in Mathematical Problem Solving — 2024 · arXiv:2405.12205
  61. 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)
  62. Mind''s Mirror: Distilling Self-Evaluation Capability and Comprehensive Thinking from Large Language Models — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  63. Mini-batch Coresets for Memory-efficient Language Model Training on Data Mixtures — 2024 · arXiv:2407.19580
  64. Mirror-Consistency: Harnessing Inconsistency in Majority Voting — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  65. Mixed Distillation Helps Smaller Language Models Reason Better — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  66. Models Can and Should Embrace the Communicative Nature of Human-Generated Math — 2024 · arXiv:2409.17005
  67. MuMath-Code: Combining Tool-Use Large Language Models with Multi-perspective Data Augmentation for Mathematical Reasoning — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  68. MuggleMath: Assessing the Impact of Query and Response Augmentation on Math Reasoning — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  69. Multi-Step Reasoning with Large Language Models, a Survey — 2024 · arXiv:2407.11511
  70. Mutual Reasoning Makes Smaller LLMs Stronger Problem-Solvers — 2024 · arXiv:2408.06195
  71. Narrative-of-Thought: Improving Temporal Reasoning of Large Language Models via Recounted Narratives — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  72. Nash CoT: Multi-Path Inference with Preference Equilibrium — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  73. Navigate through Enigmatic Labyrinth A Survey of Chain of Thought Reasoning: Advances, Frontiers and Future — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  74. Neuro-Symbolic Data Generation for Math Reasoning — 2024 · arXiv:2412.04857
  75. Not All Votes Count! Programs as Verifiers Improve Self-Consistency of Language Models for Math Reasoning — 2024 · arXiv:2410.12608
  76. NumHG: A Dataset for Number-Focused Headline Generation — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  77. Number Cookbook: Number Understanding of Language Models and How to Improve It — 2024 · arXiv:2411.03766
  78. OpenMathInstruct-1: A 1.8 Million Math Instruction Tuning Dataset — 2024 · arXiv:2402.10176
  79. Orca-Math: Unlocking the potential of SLMs in Grade School Math — 2024 · arXiv:2402.14830
  80. PLUG: Leveraging Pivot Language in Cross-Lingual Instruction Tuning — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  81. PaD: Program-aided Distillation Can Teach Small Models Reasoning Better than Chain-of-thought Fine-tuning — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  82. Personality Alignment of Large Language Models — 2024 · arXiv:2408.11779
  83. Plum: Prompt Learning using Metaheuristics — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  84. Prompt Optimization via Adversarial In-Context Learning — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  85. Prompt Space Optimizing Few-shot Reasoning Success with Large Language Models — 2024 · Findings of the Association for Computational Linguistics: NAACL 2024
  86. Putting Context in Context: the Impact of Discussion Structure on Text Classification — 2024 · Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics (Volume 1: Long Papers)
  87. Python is Not Always the Best Choice: Embracing Multilingual Program of Thoughts — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  88. Quantifying Uncertainty in Answers from any Language Model and Enhancing their Trustworthiness — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  89. RESPROMPT: Residual Connection Prompting Advances Multi-Step Reasoning in Large Language Models — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  90. 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)
  91. Re-Reading Improves Reasoning in Large Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  92. ReFT: Reasoning with Reinforced Fine-Tuning — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  93. ReFT: Representation Finetuning for Language Models — 2024 · arXiv:2404.03592
  94. Reasoning or a Semblance of it? A Diagnostic Study of Transitive Reasoning in LLMs — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  95. Reranking Laws for Language Generation: A Communication-Theoretic Perspective — 2024 · arXiv:2409.07131
  96. ResLoRA: Identity Residual Mapping in Low-Rank Adaption — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  97. Retrieved In-Context Principles from Previous Mistakes — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  98. Rho-1: Not All Tokens Are What You Need — 2024 · arXiv:2404.07965
  99. RoseLoRA: Row and Column-wise Sparse Low-rank Adaptation of Pre-trained Language Model for Knowledge Editing and Fine-tuning — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  100. S3Prompt: Instructing the Model with Self-calibration, Self-recall and Self-aggregation to Improve In-context Learning — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)

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