1 citations · 1 across the 3 of their papers we have counts for
3 papers
cs.CL2025
Testing the assumptions about the geometry of sentence embedding spaces: the cosine measure need not apply
Vivi Nastase, Paola Merlo
Transformer models learn to encode and decode an input text, and produce contextual token embeddings as a side-effect. The mapping from language into the embedding space maps words…
cs.CL2024
Are there identifiable structural parts in the sentence embedding whole?
Vivi Nastase, Paola Merlo
Sentence embeddings from transformer models encode in a fixed length vector much linguistic information. We explore the hypothesis that these embeddings consist of overlapping laye…
cs.CL2014★ 1 cited
Coarse-grained Cross-lingual Alignment of Comparable Texts with Topic Models and Encyclopedic Knowledge
Vivi Nastase, Angela Fahrni
We present a method for coarse-grained cross-lingual alignment of comparable texts: segments consisting of contiguous paragraphs that discuss the same theme (e.g. history, economy)…