受到现实生活的启发，我们想要去用attributes来改进已有的提示形式，于是就提出了<ATPrompt: Textual Prompt Learning with Embedded Attributes>。 特别地，我们的方法 重构 了自从CoOp以来提出的提示学习范式，提出了在软词元中嵌入固定的属性词元，将其作为整体输入进文本 ...

We introduce an attribute-templated prompt learning method for VLMs that utilizes universal attributes to regularize the learning of soft prompts. (2). We introduce a differentiable attribute search method that learns to determine the appropriate attribute content and quantity. (3).

2025年4月3日 · Key Attributes in Prompt Engineering. When crafting effective prompts, consider the following attributes: Clarity: Ensure that the prompt is straightforward and unambiguous. Context: Provide sufficient background information to help the model understand the task. Relevance: Include only the necessary details that pertain to the task at hand.

Due to the way OpenAI models are trained, there are specific prompt formats that work particularly well and lead to more useful model outputs. The official prompt engineering guide by OpenAI is usually the best place to start for prompting tips.

2024年4月8日 · Here are all example prompts easily to copy, adapt and use for yourself (external link, LinkedIn) and here is a handy PDF version of the cheat sheet (external link, BP) to take with you. The...

4 天之前 · In prompt engineering, attributes play a crucial role in shaping the effectiveness of the prompts used to interact with language models. Understanding these attributes can significantly enhance the quality of the generated responses. Here, we delve into the key attributes that influence prompt engineering and how they can be effectively utilized.

Attributes in prompt engineering are specific elements or parameters that can be used to control and fine-tune the responses of an AI model. They help define the context, style, and constraints within which the model operates.

A prompt contains any of the following elements: Instruction - a specific task or instruction you want the model to perform Context - external information or additional context that can steer the model to better responses

Prompt engineering is the practice of writing clear instructions that tell AI language models exactly what you want them to do. It combines careful word choice, structured formatting, and strategic examples to consistently get high-quality outputs from AI systems.

2023年12月8日 · Prompts can follow a zero, single, or few-shot learning approach. Zero-Shot is simply asking the model to perform a certain task and expecting the model to understand how it should answer and what is being asked.