From 2f36fda6ff304aa984fa22188581fbde44236896 Mon Sep 17 00:00:00 2001 From: Rabie Sadoq Date: Tue, 7 Feb 2023 19:50:59 +0100 Subject: [PATCH 1/2] Update prompts-basic-usage.md The removed sentence is the generated output --- guides/prompts-basic-usage.md | 5 +---- 1 file changed, 1 insertion(+), 4 deletions(-) diff --git a/guides/prompts-basic-usage.md b/guides/prompts-basic-usage.md index 51cdb80..9ece7e5 100644 --- a/guides/prompts-basic-usage.md +++ b/guides/prompts-basic-usage.md @@ -50,9 +50,6 @@ Here is an example of a prompt that extracts information from a given paragraph. Author-contribution statements and acknowledgements in research papers should state clearly and specifically whether, and to what extent, the authors used AI technologies such as ChatGPT in the preparation of their manuscript and analysis. They should also indicate which LLMs were used. This will alert editors and reviewers to scrutinize manuscripts more carefully for potential biases, inaccuracies and improper source crediting. Likewise, scientific journals should be transparent about their use of LLMs, for example when selecting submitted manuscripts. Mention the large language model based product mentioned in the paragraph above: - -The large language model based product mentioned in the paragraph above is ChatGPT. - ``` Output @@ -245,4 +242,4 @@ Sum: 41 Much better, right? By the way, I tried this a couple of times and the system sometime fails. If you provide a better instruction combined with examples, it might help get more accurate results. -In the upcoming guides, we will cover even more advanced prompt engineering concepts for improving performance on all these and more difficult tasks. \ No newline at end of file +In the upcoming guides, we will cover even more advanced prompt engineering concepts for improving performance on all these and more difficult tasks. From 231ab72c3959b3ea3a4d3ebf965666fbc5c901bc Mon Sep 17 00:00:00 2001 From: Elvis Saravia Date: Tue, 7 Feb 2023 20:37:04 -0600 Subject: [PATCH 2/2] Update README.md --- README.md | 3 +++ 1 file changed, 3 insertions(+) diff --git a/README.md b/README.md index 0ffcd5b..cc8f549 100644 --- a/README.md +++ b/README.md @@ -40,6 +40,7 @@ The following are a set of guides on prompt engineering developed by us. Guides - [Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing](https://arxiv.org/abs/2107.13586) (Jul 2021) - Approaches/Techniques: + - [Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery](https://arxiv.org/abs/2302.03668) (Feb 2023) - [Multimodal Chain-of-Thought Reasoning in Language Models](https://arxiv.org/abs/2302.00923) (Feb 2023) - [Large Language Models Can Be Easily Distracted by Irrelevant Context](https://arxiv.org/abs/2302.00093) (Feb 2023) - [Synthetic Prompting: Generating Chain-of-Thought Demonstrations for Large Language Models](https://arxiv.org/abs/2302.00618) (Feb 2023) @@ -89,7 +90,9 @@ The following are a set of guides on prompt engineering developed by us. Guides - [How Can We Know What Language Models Know?](https://direct.mit.edu/tacl/article/doi/10.1162/tacl_a_00324/96460/How-Can-We-Know-What-Language-Models-Know) (July 2020) - Applications: + - [PLACES: Prompting Language Models for Social Conversation Synthesis](https://arxiv.org/abs/2302.03269) (Feb 2023) - [Commonsense-Aware Prompting for Controllable Empathetic Dialogue Generation](https://arxiv.org/abs/2302.01441) (Feb 2023) + - [Crawling the Internal Knowledge-Base of Language Models](https://arxiv.org/abs/2301.12810) (Jan 2023) - [Legal Prompt Engineering for Multilingual Legal Judgement Prediction](https://arxiv.org/abs/2212.02199) (Dec 2022) - [Investigating Prompt Engineering in Diffusion Models](https://arxiv.org/abs/2211.15462) (Nov 2022) - [Conversing with Copilot: Exploring Prompt Engineering for Solving CS1 Problems Using Natural Language](https://arxiv.org/abs/2210.15157) (Oct 2022)