From f41fdced9ac66d47054ac98db755bc6ee6d7b005 Mon Sep 17 00:00:00 2001 From: trigaten Date: Sun, 15 Jan 2023 00:17:36 -0500 Subject: [PATCH 1/2] Update README.md --- README.md | 1 + 1 file changed, 1 insertion(+) diff --git a/README.md b/README.md index 789d7cf..da9a31a 100644 --- a/README.md +++ b/README.md @@ -17,6 +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 - 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) From 7428b3f3d42755cc27eb3dbb079449e03e84ae5b Mon Sep 17 00:00:00 2001 From: trigaten Date: Sun, 15 Jan 2023 00:18:12 -0500 Subject: [PATCH 2/2] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index da9a31a..c79f5e0 100644 --- a/README.md +++ b/README.md @@ -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)