Steer LLM outputs towards a certain topic/subject and enhance response capabilities using activation engineering by adding steering vectors, now in oobabooga text generation webui!
This paper surveys different prompt engineering techniques used to improve the performance of large language models on various Natural Language Processing (NLP) tasks. It categorizes these techniques by NLP task, highlights their performance on different datasets, and discusses state-of-the-art methods for specific datasets. The survey covers 44 research papers exploring 39 prompting methods across 29 NLP tasks.
An article on how to properly prompt the Mistral AI Instruct models, explaining the role of BOS, INST, and other special tokens.
How simple prompt engineering can replace custom software
This article by Kory Becker, a software developer, shares insights about prompt engineering, a crucial skill in working with large language models, gained from his AI certification.
An article discussing the current state, recent approaches, and future directions of prompt engineering in data and machine learning. It includes several links to relevant articles and tutorials on the topic.
Learn about how to prompt Command R: Understand the structured prompts used for RAG, formatting chat history and tool outputs, and changing sections of the prompt for different tasks.
A mixture of reflections, literature reviews and an experiment on Automated Prompt Engineering for Large Language Models
This article introduces a practical agent-engineering framework for the development of AI agents, focusing on the key ideas and precepts within the large language model (LLM) context.
An article discussing the concept of monosemanticity in LLMs (Language Learning Models) and how Anthropic is working on making them more controllable and safer through prompt and activation engineering.
