3 papers
cs.CL2026
Representation Collapse in Machine Translation Through the Lens of Angular Dispersion
Evgeniia Tokarchuk, Maya K. Nachesa, Sergey Troshin +1
Modern neural translation models based on the Transformer architecture are known for their high performance, particularly when trained on high-resource datasets. A standard next-to…
cs.CL2025
Angular Dispersion Accelerates -Nearest Neighbors Machine Translation
Evgeniia Tokarchuk, Sergey Troshin, Vlad Niculae
Augmenting neural machine translation with external memory at decoding time, in the form of k-nearest neighbors machine translation (-NN MT), is a well-established strategy for…
cs.LG2025
Keep your distance: learning dispersed embeddings on
Evgeniia Tokarchuk, Hua Chang Bakker, Vlad Niculae
Learning well-separated features in high-dimensional spaces, such as text or image embeddings, is crucial for many machine learning applications. Achieving such separation can be e…