# Prefix Tuning

> Prefix tuning learns continuous task-specific vectors that are prepended to the activations at every layer of a frozen language model, steering generation without changing the model's weights.

- Identifier: PTL-0077
- Category: Prompt Optimization
- Canonical URL: https://protologue.com/t/prefix-tuning/
- Introduced: 2021

## Description

It was an early parameter-efficient alternative to fine-tuning for generation tasks such as table-to-text and summarization.

## Related terms

- [Prompt Tuning](https://protologue.com/t/prompt-tuning/)
- [Low-Rank Adaptation](https://protologue.com/t/low-rank-adaptation/)

## Sources

- Li & Liang (2021). Prefix-Tuning: Optimizing Continuous Prompts for Generation. https://arxiv.org/abs/2101.00190

## Cite this entry

Protologue. (2026). Prefix Tuning. In Protologue: A Taxonomy of Prompting and LLM Techniques (v1.0.0, PTL-0077). https://protologue.com/t/prefix-tuning/

License: CC BY 4.0 (https://creativecommons.org/licenses/by/4.0/)