Papers by Tomáš Musil

2 papers
Exploring Interpretability of Independent Components of Word Embeddings with Automated Word Intruder Test (2024.lrec-main)

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Challenge: Independent Component Analysis (ICA) is an algorithm for finding separate sources in a mixed signal.
Approach: They propose to use ICA to analyze word embeddings to quantify interpretability . they propose to automate word intruder test to quantify the components .
Outcome: The proposed algorithm can be used to find semantic features of words . it can be combined to find words that have features associated with the components .
Representations of Meaning in Neural Networks for NLP: a Thesis Proposal (2021.naacl-srw)

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Challenge: Neural networks are the state-of-the-art method of machine learning for many problems in NLP.
Approach: They propose to examine the distribution of meaning in the vector space representation of words in neural networks trained for NLP tasks.
Outcome: The proposed method would be compatible with distributional hypothesis, structuralism, and semantic holism.

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