Prompt Tuning

The Power of Scale for Parameter-Efficient Prompt Tuning

Basic Workflow of Prompt

Prompt Decomposition

Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing

Example of a Complete Prompt for Machine Translation

Importance of Prompting for Response Quality

Prompting as a Conditional Probability Task

Constraining LLM Predictions to a Predefined Label Set

Prompt Ensembling

Structural Components of a Simple Prompt

Input Embeddings in LLMs

Input Token Sequence in Language Models

Varied Usage of the Term 'Prompt' in Literature

Definition of Prompting

A user provides the following text to a language model: 'Summarize the key points of the following article in three bullet points. Article: [Text of a long article follows here...]'. The model then generates a three-point summary. Based on the formal definition of how these models process information, which of the following best describes the 'prompt' in this interaction?

Analyzing the Components of a Model Input

Classification via Cloze Task Reframing

A language model is given the input text, 'Translate the following sentence to French: The cat is on the mat.' The model's objective is to generate the most likely sequence of words that completes this task. According to the formal, probabilistic definition of how these models operate, what is the fundamental role of the input text?