Exploring Interpretability of Independent Components of Word Embeddings with Automated Word Intruder Test

Tomáš Musil, David Mareček

Abstract
Independent Component Analysis (ICA) is an algorithm originally developed for finding separate sources in a mixed signal, such as a recording of multiple people in the same room speaking at the same time. Unlike Principal Component Analysis (PCA), ICA permits the representation of a word as an unstructured set of features, without any particular feature being deemed more significant than the others. In this paper, we used ICA to analyze word embeddings. We have found that ICA can be used to find semantic features of the words and these features can easily be combined to search for words that satisfy the combination. We show that most of the independent components represent such features. To quantify the interpretability of the components, we use the word intruder test, performed both by humans and by large language models. We propose to use the automated version of the word intruder test as a fast and inexpensive way of quantifying vector interpretability without the need for human effort.
Anthology ID:
2024.lrec-main.605
Volume:
Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
Month:
May
Year:
2024
Address:
Torino, Italia
Editors:
Nicoletta Calzolari, Min-Yen Kan, Veronique Hoste, Alessandro Lenci, Sakriani Sakti, Nianwen Xue
Venues:
LREC | COLING
SIG:
Publisher:
ELRA and ICCL
Note:
Pages:
6922–6928
Language:
URL:
https://aclanthology.org/2024.lrec-main.605
DOI:
Bibkey:
Cite (ACL):
Tomáš Musil and David Mareček. 2024. Exploring Interpretability of Independent Components of Word Embeddings with Automated Word Intruder Test. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 6922–6928, Torino, Italia. ELRA and ICCL.
Cite (Informal):
Exploring Interpretability of Independent Components of Word Embeddings with Automated Word Intruder Test (Musil & Mareček, LREC-COLING 2024)
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https://preview.aclanthology.org/nschneid-patch-2/2024.lrec-main.605.pdf
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