🔗 Who cites «Teaching Algorithmic Reasoning via In-context Learning»

73 papers of our library cite it (of the 149,439 whose bibliographies we read) · 23 with a page here, the most cited first · ← back to «Teaching Algorithmic Reasoning via In-context Learning»

1. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
2. A Survey on In-context LearningarXiv:2301.00234Qingxiu Dong, Lei Li, Damai Dai, et al.2023 · 978 citations
3. Towards Reasoning in Large Language Models: A SurveyFindings of the Association for Computational LinguisticsJie Huang, Kevin Chen-Chuan Chang2023 · 780 citations
4. Unleashing the potential of prompt engineering for large language modelsarXiv:2310.14735 · Patterns 6(6) 101,260 (2025)Banghao Chen, Zhaofeng Zhang, Nicolas Langrene, et al.2023 · 536 citations
5. Faith and Fate: Limits of Transformers on CompositionalityConference on Neural Information Processing Systems (NeurIPS)Nouha Dziri, Ximing Lu, Melanie Sclar, et al.2023 · 327 citations
6. Llemma: An Open Language Model For MathematicsarXiv:2310.10631Zhangir Azerbayev, Hailey Schoelkopf, Keiran Paster, et al.2023 · 286 citations
7. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
8. Deductive Verification of Chain-of-Thought ReasoningConference on Neural Information Processing Systems (NeurIPS)Zhan Ling, Yunhao Fang, Xuanlin Li, et al.2023 · 130 citations
9. Can Language Models Solve Graph Problems in Natural Language?Conference on Neural Information Processing Systems (NeurIPS)Heng Wang, Shangbin Feng, Tianxing He, et al.2023 · 124 citations
10. Quiet-STaR: Language models can teach themselves to think before speaking2024 · 122 citations
11. Complementary Explanations for Effective In-Context LearningFindings of the Association for Computational LinguisticsXi Ye, Srinivasan Iyer, Asli Celikyilmaz, et al.2023 · 106 citations
12. The Illusion of Thinking: Understanding the Strengths and Limitations of Reasoning Models via the Lens of Problem ComplexityConference on Neural Information Processing Systems (NeurIPS)Parshin Shojaee, Iman Mirzadeh, Keivan Alizadeh, et al.2025 · 104 citations
13. LAMBADA: Backward Chaining for Automated Reasoning in Natural LanguageAnnual Meeting of the Association for Computational Linguistics (ACL)Mehran Kazemi, Najoung Kim, Deepti Bhatia, et al.2023 · 89 citations
14. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
15. What Algorithms can Transformers Learn? A Study in Length GeneralizationarXiv:2310.16028Hattie Zhou, Arwen Bradley, Etai Littwin, et al.2023 · 67 citations
16. Goat: Fine-tuned LLaMA Outperforms GPT-4 on Arithmetic TasksarXiv:2305.14201Tiedong Liu, Bryan Kian Hsiang Low2023 · 65 citations
17. Teaching Arithmetic to Small TransformersarXiv:2307.03381Nayoung Lee, Kartik Sreenivasan, Jason D. Lee, et al.2023 · 57 citations
18. Parsel: Algorithmic Reasoning with Language Models by Composing DecompositionsConference on Neural Information Processing Systems (NeurIPS)Eric Zelikman, Qian Huang, Gabriel Poesia, et al.2023 · 56 citations
19. Tokenization counts: the impact of tokenization on arithmetic in frontier LLMsarXiv:2402.14903Aaditya K. Singh, DJ Strouse2024 · 55 citations
20. Reasoning Abilities of Large Language Models: In-Depth Analysis on the Abstraction and Reasoning CorpusACM Transactions on Intelligent Systems and TechnologySeungpil Lee, Woochang Sim, Donghyeon Shin, et al.2024 · 38 citations
21. Skills-in-Context Prompting: Unlocking Compositionality in Large Language ModelsarXiv:2308.00304Jiaao Chen, Xiaoman Pan, Dian Yu, et al.2023 · 17 citations
22. CAST: Achieving Stable LLM-based Text Analysis for Data AnalyticsFindings of the Association for Computational LinguisticsJinxiang Xie, Zihao Li, Wei He, et al.2026
23. Evidence-Augmented Generation Reasoning for Extremely Low-Resource Language DeciphermentWorkshop on Multilinguality in the Era of Large Language ModelsXiaoyu Zhu, Long Yuan, Rui Qi, et al.2026

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