--- title: "Who cites Large Language Models as Analogical Reasoners" description: "62 papers of the Elamur Research library cite «Large Language Models as Analogical Reasoners», found in their bibliographies; the most cited first." canonical: "https://research.elamur.ai/free/en/papers/yasunaga-2023-large-language-models-analogical-reasoners/cited-by/" --- [Elamur Research](https://md.research.elamur.ai/free/en/) · [this page in HTML](https://research.elamur.ai/free/en/papers/yasunaga-2023-large-language-models-analogical-reasoners/cited-by/) [home](https://md.research.elamur.ai/free/en/) / [papers](https://md.research.elamur.ai/free/en/papers/) / [Large Language Models as Analogical Reasoners](https://md.research.elamur.ai/free/en/papers/yasunaga-2023-large-language-models-analogical-reasoners/) / cited by # Who cites «Large Language Models as Analogical Reasoners» 62 papers of our library cite it (of the 149,439 whose bibliographies we read) · 12 with a page here, the most cited first · [← back to «Large Language Models as Analogical Reasoners»](https://md.research.elamur.ai/free/en/papers/yasunaga-2023-large-language-models-analogical-reasoners/) 1. [**LiveCodeBench: Holistic and Contamination Free Evaluation of Large Language Models for Code arXiv:2403.07974**Naman Jain, King Han, Alex Gu, et al.*2024 · 578 citations*](https://md.research.elamur.ai/free/en/papers/jain-2024-livecodebench-holistic-contamination-free-evaluation/) 2. [**Can LLMs Generate Novel Research Ideas? A Large-Scale Human Study with 100+ NLP Researchers arXiv:2409.04109**Chenglei Si, Diyi Yang, Tatsunori Hashimoto*2024 · 196 citations*](https://md.research.elamur.ai/free/en/papers/si-2024-llms-generate-novel-research/) 3. [**The Prompt Report: A Systematic Survey of Prompt Engineering Techniques arXiv:2406.06608**Sander Schulhoff, Michael Ilie, Nishant Balepur, et al.*2024 · 189 citations*](https://md.research.elamur.ai/free/en/papers/schulhoff-2024-prompt-report-systematic-survey-prompt/) 4. **[LINC: A Neurosymbolic Approach for Logical Reasoning by Combining Language Models with First-Order Logic Provers](https://md.research.elamur.ai/free/en/papers/olausson-2023-linc-neurosymbolic-approach-logical-reasoning/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Theo X. Olausson, Alex Gu, Benjamin Lipkin, et al.*2023 · 172 citations* 5. **[Buffer of Thoughts: Thought-Augmented Reasoning with Large Language Models](https://md.research.elamur.ai/free/en/papers/yang-2024-buffer-thoughts-thought-augmented-reasoning/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Ling Yang, Zhaochen Yu, Tianjun Zhang, et al.*2024 · 67 citations* 6. **[AutoPSV: Automated Process-Supervised Verifier](https://md.research.elamur.ai/free/en/papers/lu-2024-autopsv-automated-process-supervised-verifier/) [Conference on Neural Information Processing Systems (NeurIPS)](https://md.research.elamur.ai/free/en/venues/neural-information-processing-systems/)**Jianqiao Lu, Zhiyang Dou, Hongru Wang, et al.*2024 · 28 citations* 7. [**Could Thinking Multilingually Empower LLM Reasoning? arXiv:2504.11833**Changjiang Gao, Xu Huang, Wenhao Zhu, et al.*2025 · 10 citations*](https://md.research.elamur.ai/free/en/papers/gao-2025-could-thinking-multilingually-empower-llm/) 8. **[GCoT-Decoding: Unlocking Deep Reasoning Paths for Universal Question Answering](https://md.research.elamur.ai/free/en/papers/luo-2026-gcot-decoding-unlocking-deep-reasoning/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Guanran Luo, Wentao Qiu, Zhongquan Jian, et al.*2026 · 6 citations* 9. **[A Comprehensive Evaluation of Chain-of-Thought Faithfulness in Persian Classification Tasks](https://md.research.elamur.ai/free/en/papers/yazdani-2026-comprehensive-evaluation-chain-thought-faithfulness/) [Workshop on Language Models for Low-Resource Languages](https://md.research.elamur.ai/free/en/venues/loreslm/)**Shakib Yazdani, Cristina España-Bonet, Eleftherios Avramidis, et al.*2026 · 1 citation* 10. **[Understanding Structured Financial Data with LLMs: A Case Study on Fraud Detection](https://md.research.elamur.ai/free/en/papers/tan-2026-understanding-structured-financial-data-llms/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Xuwei Tan, Yao Ma, Xueru Zhang*2026 · 1 citation* 11. **[Can LLMs Reason Like Doctors? Exploring the Limits of Large Language Models in Complex Medical Reasoning](https://md.research.elamur.ai/free/en/papers/merenda-2026-can-llms-reason-like-doctors/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Flavio Merenda, Jose Manuel Gomez-Perez, German Rigau*2026* 12. **[CheckRLM: Effective Knowledge–Thought Coherence Checking in Retrieval-Augmented Reasoning](https://md.research.elamur.ai/free/en/papers/xu-2026-checkrlm-effective-knowledge-thought-coherence/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Dingling Xu, Ruobing Wang, Qingfei Zhao, et al.*2026* 50 more papers of our library cite it; they have no page here yet. - [← back to](https://md.research.elamur.ai/free/en/papers/yasunaga-2023-large-language-models-analogical-reasoners/) — Large Language Models as Analogical Reasoners