Which LLM said that? - watermarking generated text
Formal Metadata
| Title | Which LLM said that? - watermarking generated text |
|
| Title of Series | |
| Number of Parts | 131 |
| Author | |
| Contributors | |
| License | You are free to use, adapt and copy, distribute and transmit the work or content in adapted or unchanged form for any legal and non-commercial purpose as long as the work is attributed to the author in the manner specified by the author or licensor and the work or content is shared also in adapted form only under the conditions of this license. |
| Identifiers | |
| Publisher | |
| Release Date | |
| Language | |
Content Metadata
| Subject Area | |
| Genre | |
| Abstract | With the emergence of large generative language models there comes a problem of assigning the authorship of the AI-generated texts to its original source. This raises many concerns regarding eg. social engineering, fake news generation and cheating in many educational assignments. While there are several black-box methods for detecting if text was written by human or LLM they have significant issues.
I will discuss how by watermarking you can equip your LLM with a mechanism that undetectable to human eye can give you the means of verifying if it was the true source of a generated text. |
|