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## Papers
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- Surveys / Overviews:
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- [Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing](https://arxiv.org/abs/2107.13586)
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- [A Taxonomy of Prompt Modifiers for Text-To-Image Generation](https://arxiv.org/abs/2204.13988)
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- [Emergent Abilities of Large Language Models](https://arxiv.org/abs/2206.07682)
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- [A Survey for In-context Learning](https://arxiv.org/pdf/2301.00234.pdf)
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- [A Survey for In-context Learning](https://arxiv.org/abs/2301.00234) (Dec 2022)
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- [Emergent Abilities of Large Language Models](https://arxiv.org/abs/2206.07682) (Jun 2022)
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- [A Taxonomy of Prompt Modifiers for Text-To-Image Generation](https://arxiv.org/abs/2204.13988) (Apr 2022)
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- [Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing](https://arxiv.org/abs/2107.13586) (Jul 2021)
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- Applications:
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- [Legal Prompt Engineering for Multilingual Legal Judgement Prediction](https://arxiv.org/abs/2212.02199)
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- [Investigating Prompt Engineering in Diffusion Models](https://arxiv.org/abs/2211.15462)
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- [Conversing with Copilot: Exploring Prompt Engineering for Solving CS1 Problems Using Natural Language](https://arxiv.org/abs/2210.15157)
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- [Piloting Copilot and Codex: Hot Temperature, Cold Prompts, or Black Magic?](https://arxiv.org/abs/2210.14699)
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- [Legal Prompt Engineering for Multilingual Legal Judgement Prediction](https://arxiv.org/abs/2212.02199) (Dec 2022)
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- [Investigating Prompt Engineering in Diffusion Models](https://arxiv.org/abs/2211.15462) (Nov 2022)
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- [Conversing with Copilot: Exploring Prompt Engineering for Solving CS1 Problems Using Natural Language](https://arxiv.org/abs/2210.15157) (Oct 2022)
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- [Piloting Copilot and Codex: Hot Temperature, Cold Prompts, or Black Magic?](https://arxiv.org/abs/2210.14699) (Oct 2022)
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- Approaches/Techniques:
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- [Batch Prompting: Efficient Inference with LLM APIs](https://arxiv.org/abs/2301.08721) (Jan 2023)
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