Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal
Article Title
Document Type
Article
Abstract
Machine learning models, while very powerful, have their operation obfuscated behind millions of parameters. This obfuscation can make deriving a human meaningful process from a machine learning model very difficult. However, while the intermediate states of a machine learning model are similarly obfuscated, using probing, we can start to explore looking at possible structure in those intermediate states. Large language models are a prime example of this obfuscation, and probing can begin to allow novel experimentation to be performed.
Recommended Citation
Plasek, Ashlen A.
(2023)
"Probing as a Technique to Understand Abstract Spaces,"
Scholarly Horizons: University of Minnesota, Morris Undergraduate Journal: Vol. 10:
Iss.
2, Article 5.
DOI: https://doi.org/10.61366/2576-2176.1126
Available at:
https://digitalcommons.morris.umn.edu/horizons/vol10/iss2/5
Primo Type
Article