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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. Parrot: A Training Pipeline Enhances Both Program CoT and Natural Language CoT for Reasoning — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  2. 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
  3. PhysicsEval: Inference-Time Techniques to Improve the Reasoning Proficiency of Large Language Models on Physics Problems — 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
  4. Predicting Through Generation: Why Generation Is Better for Prediction — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  5. Prejudge-Before-Think: Enhancing Large Language Models at Test-Time by Process Prejudge Reasoning — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
  6. 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
  7. Probing for Arithmetic Errors in Language Models — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  8. Problem-Solving Logic Guided Curriculum In-Context Learning for LLMs Complex Reasoning — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  9. PromptWizard: Optimizing Prompts via Task-Aware, Feedback-Driven Self-Evolution — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  10. Propulsion: Steering LLM with Tiny Fine-Tuning — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
  11. QCRD: Quality-guided Contrastive Rationale Distillation for Large Language Models — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  12. RRInf: Efficient Influence Function Estimation via Ridge Regression for Large Language Models and Text-to-Image Diffusion Models — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  13. Rationales Are Not Silver Bullets: Measuring the Impact of Rationales on Model Performance and Reliability — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  14. Reason from Future: Reverse Thought Chain Enhances LLM Reasoning — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  15. Reasoning Graph Enhanced Exemplars Retrieval for In-Context Learning — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
  16. Reasoning with Latent Thoughts: On the Power of Looped Transformers — 2025 · arXiv:2502.17416
  17. Recursive Decomposition of Logical Thoughts: Framework for Superior Reasoning and Knowledge Propagation in Large Language Models — 2025 · arXiv:2501.02026
  18. Revisiting Test-Time Scaling: A Survey and a Diversity-Aware Method for Efficient Reasoning — 2025 · arXiv:2506.04611
  19. 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)
  20. SIKeD: Self-guided Iterative Knowledge Distillation for Mathematical Reasoning — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  21. SKYLENAGE Technical Report: Mathematical Reasoning and Contest-Innovation Benchmarks for Multi-Level Math Evaluation — 2025 · arXiv:2510.01241
  22. SafeSieve: From Heuristics to Experience in Progressive Pruning for LLM-based Multi-Agent Communication — 2025 · arXiv:2508.11733
  23. SalaMAnder: Shapley-based Mathematical Expression Attribution and Metric for Chain-of-Thought Reasoning — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
  24. 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)
  25. Semantic Exploration with Adaptive Gating for Efficient Problem Solving with Language Models — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  26. Sketch-of-Thought: Efficient LLM Reasoning with Adaptive Cognitive-Inspired Sketching — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  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. Soft Reasoning: Navigating Solution Spaces in Large Language Models through Controlled Embedding Exploration — 2025 · arXiv:2505.24688
  29. Solving Math Word Problems Using Estimation Verification and Equation Generation — 2025 · arXiv:2509.18565
  30. Step-by-Step Unmasking for Parameter-Efficient Fine-Tuning of Large Language Models — 2025 · Transactions of the Association for Computational Linguistics
  31. Structured Moral Reasoning in Language Models: A Value-Grounded Evaluation Framework — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  32. Subtle Errors in Reasoning: Preference Learning via Error-injected Self-editing — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  33. Superficial Self-Improved Reasoners Benefit from Model Merging — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  34. Syntactic Blind Spots: How Misalignment Leads to LLMs'' Mathematical Errors — 2025 · Proceedings of The 3rd Workshop on Mathematical Natural Language Processing (MathNLP 2025)
  35. Task Calibration: Calibrating Large Language Models on Inference Tasks — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  36. Teaching-Inspired Integrated Prompting Framework: A Novel Approach for Enhancing Reasoning in Large Language Models — 2025 · Proceedings of the 31st International Conference on Computational Linguistics: Industry Track
  37. Theorem Prover as a Judge for Synthetic Data Generation — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  38. Think Silently, Think Fast: Dynamic Latent Compression of LLM Reasoning Chains — 2025 · arXiv:2505.16552
  39. ThoughtProbe: Classifier-Guided LLM Thought Space Exploration via Probing Representations — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  40. Tiny Budgets, Big Gains: Parameter Placement Strategy in Parameter Super-Efficient Fine-Tuning — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  41. Token-Efficient RL for LLM Reasoning — 2025 · arXiv:2504.20834
  42. Towards Efficient CoT Distillation: Self-Guided Rationale Selector for Better Performance with Fewer Rationales — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
  43. Towards Faithful Multi-step Reasoning through Fine-Grained Causal-aware Attribution Reasoning Distillation — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
  44. Towards Robust Mathematical Reasoning — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  45. UBench: Benchmarking Uncertainty in Large Language Models with Multiple Choice Questions — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  46. UNDO: Understanding Distillation as Optimization — 2025 · arXiv:2504.02521
  47. 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)
  48. UTMath: A Benchmark for Math Evaluation with Unit Test — 2025 · Findings of the Association for Computational Linguistics: EMNLP 2025
  49. Uncertainty-Aware Contrastive Decoding — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  50. Understand, Solve and Translate: Bridging the Multilingual Mathematical Reasoning Gap — 2025 · Proceedings of the 5th Workshop on Multilingual Representation Learning (MRL 2025)
  51. Understanding the Information Propagation Effects of Communication Topologies in LLM-based Multi-Agent Systems — 2025 · Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing
  52. Unveiling the Key Factors for Distilling Chain-of-Thought Reasoning — 2025 · Findings of the Association for Computational Linguistics: ACL 2025
  53. 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
  54. Velocitune: A Velocity-based Dynamic Domain Reweighting Method for Continual Pre-training — 2025 · Proceedings of the 63rd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  55. Weak-for-Strong: Training Weak Meta-Agent to Harness Strong Executors — 2025 · arXiv:2504.04785
  56. When natural language is not enough: The limits of in-context learning demonstrations in multilingual reasoning — 2025 · Findings of the Association for Computational Linguistics: NAACL 2025
  57. Zero-to-Strong Generalization: Eliciting Strong Capabilities of Large Language Models Iteratively without Gold Labels — 2025 · Proceedings of the 31st International Conference on Computational Linguistics
  58. 基于思维链和知识迁移的多语言问答推理研究 — 2025 · Proceedings of the 24th China National Conference on Computational Linguistics (CCL 2025)
  59. 3-in-1: 2D Rotary Adaptation for Efficient Finetuning, Efficient Batching and Composability — 2024 · arXiv:2409.00119
  60. A Symbolic Framework for Evaluating Mathematical Reasoning and Generalisation with Transformers — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  61. API-BLEND: A Comprehensive Corpora for Training and Benchmarking API LLMs — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  62. AdaSwitch: Adaptive Switching between Small and Large Agents for Effective Cloud-Local Collaborative Learning — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  63. 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
  64. Advancing LLM Reasoning Generalists with Preference Trees — 2024 · arXiv:2404.02078
  65. Agent Lumos: Unified and Modular Training for Open-Source Language Agents — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  66. 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)
  67. Alice in Wonderland: Simple Tasks Showing Complete Reasoning Breakdown in State-Of-the-Art Large Language Models — 2024 · arXiv:2406.02061
  68. AlignedCoT: Prompting Large Language Models via Native-Speaking Demonstrations — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  69. AlphaLoRA: Assigning LoRA Experts Based on Layer Training Quality — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  70. An Empirical Study of Data Ability Boundary in LLMs' Math Reasoning — 2024 · arXiv:2403.00799
  71. ApiQ: Finetuning of 2-Bit Quantized Large Language Model — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  72. Ask Again, Then Fail: Large Language Models'' Vacillations in Judgment — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  73. Automated Design of Agentic Systems — 2024 · arXiv:2408.08435
  74. Benchmarking Hallucination in Large Language Models Based on Unanswerable Math Word Problem — 2024 · Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
  75. Better Zero-Shot Reasoning with Role-Play Prompting — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers)
  76. Beyond Chinchilla-Optimal: Accounting for Inference in Language Model Scaling Laws — 2024 · arXiv:2401.00448
  77. Beyond Lines and Circles: Unveiling the Geometric Reasoning Gap in Large Language Models — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  78. Boosting Language Models Reasoning with Chain-of-Knowledge Prompting — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
  79. Breaking Language Barriers in Multilingual Mathematical Reasoning: Insights and Observations — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  80. COAT: Compressing Optimizer states and Activation for Memory-Efficient FP8 Training — 2024 · arXiv:2410.19313
  81. Calc-CMU at SemEval-2024 Task 7: Pre-Calc - Learning to Use the Calculator Improves Numeracy in Language Models — 2024 · Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
  82. Can LLMs Learn From Mistakes? An Empirical Study on Reasoning Tasks — 2024 · Findings of the Association for Computational Linguistics: EMNLP 2024
  83. Can Language Models Rival Mathematics Students? Evaluating Mathematical Reasoning through Textual Manipulation and Human Experiments — 2024 · arXiv:2412.11908
  84. Chain-of-Translation Prompting (CoTR): A Novel Prompting Technique for Low Resource Languages — 2024 · Proceedings of the 38th Pacific Asia Conference on Language, Information and Computation
  85. Code Prompting Elicits Conditional Reasoning Abilities in Text+Code LLMs — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  86. Common 7B Language Models Already Possess Strong Math Capabilities — 2024 · arXiv:2403.04706
  87. Competition-Level Problems are Effective LLM Evaluators — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  88. ConceptMath: A Bilingual Concept-wise Benchmark for Measuring Mathematical Reasoning of Large Language Models — 2024 · Findings of the Association for Computational Linguistics: ACL 2024
  89. ControlMath: Controllable Data Generation Promotes Math Generalist Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  90. Cutting Through the Noise: Boosting LLM Performance on Math Word Problems — our card · 2024 · arXiv:2406.15444
  91. DDPrompt: Differential Diversity Prompting in Large Language Models — 2024 · Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
  92. Data Augmentation with In-Context Learning and Comparative Evaluation in Math Word Problem Solving — 2024 · arXiv:2404.03938 · SN Computer Science, 5, 506 (2024)
  93. DataComp-LM: In search of the next generation of training sets for language models — 2024 · arXiv:2406.11794
  94. Decoding with Limited Teacher Supervision Requires Understanding When to Trust the Teacher — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  95. DeepSeek-Coder: When the Large Language Model Meets Programming -- The Rise of Code Intelligence — 2024 · arXiv:2401.14196
  96. Dictionary Insertion Prompting for Multilingual Reasoning on Multilingual Large Language Models — 2024 · arXiv:2411.01141
  97. 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)
  98. DynaThink: Fast or Slow? A Dynamic Decision-Making Framework for Large Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing
  99. EchoPrompt: Instructing the Model to Rephrase Queries for Improved In-context Learning — 2024 · Proceedings of the 2024 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 2: Short Papers)
  100. Empowering Multi-step Reasoning across Languages via Program-Aided Language Models — 2024 · Proceedings of the 2024 Conference on Empirical Methods in Natural Language Processing

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