🔗 Who cites «Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data»

68 papers of our library cite it (of the 141,840 whose bibliographies we read) · 6 with a page here, the most cited first · ← back to «Automatic Prompt Augmentation and Selection with Chain-of-Thought from Labeled Data»

1. 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
   Towards Reasoning Era: A Survey of Long Chain-of-Thought for Reasoning Large Language ModelsScience China Information SciencesQiguang Chen, Libo Qin, Jinhao Liu, et al.2025 · 174 citations
2. Promptbreeder: Self-Referential Self-Improvement Via Prompt EvolutionarXiv:2309.16797Chrisantha Fernando, Dylan Banarse, Henryk Michalewski, et al.2023 · 165 citations
3. Reasoning with Language Model Prompting: A SurveyarXiv:2212.09597Shuofei Qiao, Yixin Ou, Ningyu Zhang, et al.2022 · 161 citations
   A Survey on Recent Advances in LLM-Based Multi-turn Dialogue SystemsACM Computing SurveysZihao Yi, Jiarui Ouyang, Zhe Xu, et al.2024 · 129 citations
   Does DetectGPT Fully Utilize Perturbation? Bridging Selective Perturbation to Fine-tuned Contrastive Learning Detector would be BetterAnnual Meeting of the Association for Computational Linguistics (ACL)Shengchao Liu, Xiaoming Liu, Yichen Wang, et al.2024 · 16 citations

62 more papers of our library cite it; they have no page here yet.

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