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@ -58,6 +58,7 @@ The following are the latest papers (sorted by release date) on prompt engineeri
- [Augmented Language Models: a Survey](https://arxiv.org/abs/2302.07842) (Feb 2023) - [Augmented Language Models: a Survey](https://arxiv.org/abs/2302.07842) (Feb 2023)
- [A Survey for In-context Learning](https://arxiv.org/abs/2301.00234) (Dec 2022) - [A Survey for In-context Learning](https://arxiv.org/abs/2301.00234) (Dec 2022)
- [Towards Reasoning in Large Language Models: A Survey](https://arxiv.org/abs/2212.10403) (Dec 2022) - [Towards Reasoning in Large Language Models: A Survey](https://arxiv.org/abs/2212.10403) (Dec 2022)
- [Reasoning with Language Model Prompting: A Survey](https://arxiv.org/abs/2212.09597) (Dec 2022)
- [Emergent Abilities of Large Language Models](https://arxiv.org/abs/2206.07682) (Jun 2022) - [Emergent Abilities of Large Language Models](https://arxiv.org/abs/2206.07682) (Jun 2022)
- [A Taxonomy of Prompt Modifiers for Text-To-Image Generation](https://arxiv.org/abs/2204.13988) (Apr 2022) - [A Taxonomy of Prompt Modifiers for Text-To-Image Generation](https://arxiv.org/abs/2204.13988) (Apr 2022)
- [Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing](https://arxiv.org/abs/2107.13586) (Jul 2021) - [Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing](https://arxiv.org/abs/2107.13586) (Jul 2021)