🧑‍🔬 Who cites Hattie Zhou

132 citations of their works from 124 papers of our library (of the 149,439 whose bibliographies we read) · 31 with a page here, the most cited first · ← Hattie Zhou

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. GSM-Symbolic: Understanding the Limitations of Mathematical Reasoning in Large Language ModelsarXiv:2410.05229Iman Mirzadeh, Keivan Alizadeh, Hooman Shahrokhi, et al.2024 · 273 citations
8. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
9. Deductive Verification of Chain-of-Thought ReasoningConference on Neural Information Processing Systems (NeurIPS)Zhan Ling, Yunhao Fang, Xuanlin Li, et al.2023 · 130 citations
10. 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
11. CRUXEval: A Benchmark for Code Reasoning, Understanding and ExecutionarXiv:2401.03065Alex Gu, Baptiste Rozière, Hugh Leather, et al.2024 · 122 citations
12. Quiet-STaR: Language models can teach themselves to think before speaking2024 · 122 citations
13. The Alignment Problem from a Deep Learning PerspectivearXiv:2209.00626Richard Ngo, Lawrence Chan, Soren Mindermann2022 · 121 citations
14. Complementary Explanations for Effective In-Context LearningFindings of the Association for Computational LinguisticsXi Ye, Srinivasan Iyer, Asli Celikyilmaz, et al.2023 · 106 citations
15. 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
16. 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
17. Foundational Challenges in Assuring Alignment and Safety of Large Language ModelsarXiv:2404.09932Usman Anwar, Abulhair Saparov, Javier Rando, et al.2024 · 87 citations
18. Rethinking Interpretability in the Era of Large Language ModelsarXiv:2402.01761Chandan Singh, Jeevana Priya Inala, Michel Galley, et al.2024 · 87 citations
19. A Primer on the Inner Workings of Transformer-based Language ModelsarXiv:2405.00208Javier Ferrando, Gabriele Sarti, Arianna Bisazza, et al.2024 · 72 citations
20. What Algorithms can Transformers Learn? A Study in Length GeneralizationarXiv:2310.16028Hattie Zhou, Arwen Bradley, Etai Littwin, et al.2023 · 67 citations
21. Goat: Fine-tuned LLaMA Outperforms GPT-4 on Arithmetic TasksarXiv:2305.14201Tiedong Liu, Bryan Kian Hsiang Low2023 · 65 citations
22. Physics of Language Models: Part 2.1, Grade-School Math and the Hidden Reasoning ProcessarXiv:2407.20311Tian Ye, Zicheng Xu, Yuanzhi Li, et al.2024 · 58 citations
23. Teaching Arithmetic to Small TransformersarXiv:2307.03381Nayoung Lee, Kartik Sreenivasan, Jason D. Lee, et al.2023 · 57 citations
24. 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
25. Tokenization counts: the impact of tokenization on arithmetic in frontier LLMsarXiv:2402.14903Aaditya K. Singh, DJ Strouse2024 · 55 citations
26. 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
27. Skills-in-Context Prompting: Unlocking Compositionality in Large Language ModelsarXiv:2308.00304Jiaao Chen, Xiaoman Pan, Dian Yu, et al.2023 · 17 citations
28. Between Circuits and Chomsky: Pre-pretraining on Formal Languages Imparts Linguistic BiasesAnnual Meeting of the Association for Computational Linguistics (ACL)Michael Y. Hu, Jackson Petty, Chuan Shi, et al.2025 · 9 citations
29. CAST: Achieving Stable LLM-based Text Analysis for Data AnalyticsFindings of the Association for Computational LinguisticsJinxiang Xie, Zihao Li, Wei He, et al.2026
30. 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
31. GSM-Noise: Exploring and Enhancing Large Language Models' Reasoning under Noisy InputsFindings of the Association for Computational LinguisticsZhengxin Zhang, Chengyu Huang, Xufu Liu, et al.2026

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