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@ -17,7 +17,7 @@ This guide contains a non-exhaustive set of learning guides and tools about prom
- [Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing](https://arxiv.org/abs/2107.13586)
- [A Taxonomy of Prompt Modifiers for Text-To-Image Generation](https://arxiv.org/abs/2204.13988)
- [Emergent Abilities of Large Language Models](https://arxiv.org/abs/2206.07682)
- [A Survey for In-context Learning](https://arxiv.org/pdf/2301.00234.pdf
- [A Survey for In-context Learning](https://arxiv.org/pdf/2301.00234.pdf)
- Applications:
- [Legal Prompt Engineering for Multilingual Legal Judgement Prediction](https://arxiv.org/abs/2212.02199)
- [Investigating Prompt Engineering in Diffusion Models](https://arxiv.org/abs/2211.15462)