🔗 Who cites «Rationale-Augmented Ensembles in Language Models»

73 papers of our library cite it (of the 149,439 whose bibliographies we read) · 29 with a page here, the most cited first · ← back to «Rationale-Augmented Ensembles in Language Models»

1. A Survey of Large Language ModelsFrontiers of Computer ScienceWayne Xin Zhao, Kun Zhou, Junyi Li, et al.2023 · 2,875 citations
2. ReAct: Synergizing Reasoning and Acting in Language ModelsarXiv:2210.03629Shunyu Yao, Jeffrey Zhao, Dian Yu, et al.2022 · 2,591 citations
3. A Comprehensive Overview of Large Language ModelsACM Transactions on Intelligent Systems and TechnologyHumza Naveed, Asad Ullah Khan, Shi Qiu, et al.2023 · 1,287 citations
4. Is ChatGPT a General-Purpose Natural Language Processing Task Solver?Conference on Empirical Methods in Natural Language Processing (EMNLP)Chengwei Qin, Aston Zhang, Zhuosheng Zhang, et al.2023 · 828 citations
5. GLM-130B: An Open Bilingual Pre-trained ModelarXiv:2210.02414Aohan Zeng, Xiao Liu, Zhengxiao Du, et al.2022 · 786 citations
6. Large Language Models Can Self-ImproveConference on Empirical Methods in Natural Language Processing (EMNLP)Jiaxin Huang, Shixiang Gu, Le Hou, et al.2023 · 575 citations
7. Large Language Models Can Be Easily Distracted by Irrelevant ContextarXiv:2302.00093Freda Shi, Xinyun Chen, Kanishka Misra, et al.2023 · 534 citations
8. Language Models are Multilingual Chain-of-Thought ReasonersarXiv:2210.03057Freda Shi, Mirac Suzgun, Markus Freitag, et al.2022 · 494 citations
9. Complexity-Based Prompting for Multi-Step ReasoningarXiv:2210.00720Yao Fu, Hao Peng, Ashish Sabharwal, et al.2022 · 345 citations
10. Multimodal Chain-of-Thought Reasoning in Language ModelsarXiv:2302.00923Zhuosheng Zhang, Aston Zhang, Mu Li, et al.2023 · 308 citations
11. DSPy: Compiling Declarative Language Model Calls into Self-Improving PipelinesarXiv:2310.03714Omar Khattab, Arnav Singhvi, Paridhi Maheshwari, et al.2023 · 285 citations
12. Measuring Faithfulness in Chain-of-Thought ReasoningarXiv:2307.13702Tamera Lanham, Anna Chen, Ansh Radhakrishnan, et al.2023 · 262 citations
13. Demonstrate-Search-Predict: Composing retrieval and language models for knowledge-intensive NLParXiv:2212.14024Omar Khattab, Keshav Santhanam, Xiang Lisa Li, et al.2022 · 222 citations
14. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
15. Symbolic Chain-of-Thought Distillation: Small Models Can Also “Think” Step-by-StepAnnual Meeting of the Association for Computational Linguistics (ACL)Liunian Harold Li, Jack Hessel, Youngjae Yu, et al.2023 · 140 citations
16. Progressive-Hint Prompting Improves Reasoning in Large Language ModelsarXiv:2304.09797Chuanyang Zheng, Zhengying Liu, Enze Xie, et al.2023 · 131 citations
17. Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled DataFindings of the Association for Computational LinguisticsKashun Shum, Shizhe Diao, Tong Zhang2023 · 128 citations
18. Complementary Explanations for Effective In-Context LearningFindings of the Association for Computational LinguisticsXi Ye, Srinivasan Iyer, Asli Celikyilmaz, et al.2023 · 106 citations
19. Teaching Algorithmic Reasoning via In-context LearningarXiv:2211.09066Hattie Zhou, Azade Nova, Hugo Larochelle, et al.2022 · 96 citations
20. Boosting Language Models Reasoning with Chain-of-Knowledge PromptingAnnual Meeting of the Association for Computational Linguistics (ACL)Jianing Wang, Qiushi Sun, Xiang Li, et al.2024 · 94 citations
21. Entailer: Answering Questions with Faithful and Truthful Chains of ReasoningConference on Empirical Methods in Natural Language Processing (EMNLP)Oyvind Tafjord, Bhavana Dalvi Mishra, Peter Clark2022 · 71 citations
22. Aligning Large and Small Language Models via Chain-of-Thought ReasoningConference of the European Chapter of the Association for Computational Linguistics (EACL)Leonardo Ranaldi, Andre Freitas2024 · 70 citations
23. “According to . . . “: Prompting Language Models Improves Quoting from Pre-Training DataConference of the European Chapter of the Association for Computational Linguistics (EACL)Orion Weller, Marc Marone, Nathaniel Weir, et al.2024 · 46 citations
24. In-Context Principle Learning from MistakesarXiv:2402.05403Tianjun Zhang, Aman Madaan, Luyu Gao, et al.2024 · 19 citations
25. GCoT-Decoding: Unlocking Deep Reasoning Paths for Universal Question AnsweringFindings of the Association for Computational LinguisticsGuanran Luo, Wentao Qiu, Zhongquan Jian, et al.2026 · 6 citations
26. Task Matters: Knowledge Requirements Shape LLM Responses to Context–Memory ConflictFindings of the Association for Computational LinguisticsKaiser Sun, Fan Bai, Mark Dredze2026 · 3 citations
27. H3Fusion: Helpful, Harmless, Honest Fusion of Aligned LLMsConference of the European Chapter of the Association for Computational Linguistics (EACL)Selim Furkan Tekin, Fatih Ilhan, Sihao Hu, et al.2026 · 1 citation
28. A Single Model Ensemble Framework for Neural Machine Translation Using Pivot TranslationLanguage Resources and Evaluation Conference (LREC)Seokjin Oh, Keonwoong Noh, Woohwan Jung2026
29. 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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