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Prompt-Engineering-Guide
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@ -32,7 +32,6 @@ This guide contains a set of papers, learning guides, and tools related to promp
- [Large Language Models Are Human-Level Prompt Engineers](https://sites.google.com/view/automatic-prompt-engineer?pli=1)
- [BERTese: Learning to Speak to BERT](https://aclanthology.org/2021.eacl-main.316/)
- [Batch Prompting: Efficient Inference with LLM APIs](https://arxiv.org/abs/2301.08721)
- [Fantastically Ordered Prompts and Where to Find Them: Overcoming Few-Shot Prompt Order Sensitivity](https://arxiv.org/abs/2104.08786)
- [Large Language Models are Zero-Shot Reasoners](https://arxiv.org/abs/2205.11916)
- [Decomposed Prompting: A Modular Approach for Solving Complex Tasks](https://arxiv.org/abs/2210.02406)
- [Successive Prompting for Decomposing Complex Questions](https://arxiv.org/abs/2212.04092)