Papers by Alexandros Vasileiou

1 papers
Explaining Text Similarity in Transformer Models (2024.naacl-long)

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Challenge: Modern foundation models provide flexible text representations that enable the detection of semantic structure in vast amounts of unlabeled data.
Approach: They propose to leverage layer-wise relevance propagation to understand the inner prediction mechanisms of NLP models by analyzing grammatical interactions, multilingual semantics, and biomedical text retrieval.
Outcome: The proposed methods demonstrate their utility in three corpus-level use cases, analyzing grammatical interactions, multilingual semantics, and biomedical text retrieval.

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