4 papers
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…
Asking a Language Model for Diverse Responses
Sergey Troshin, Irina Saparina, Antske Fokkens +1
Large language models increasingly rely on explicit reasoning chains and can produce multiple plausible responses for a given context. We study the candidate sampler that produces…
Control the Temperature: Selective Sampling for Diverse and High-Quality LLM Outputs
Sergey Troshin, Wafaa Mohammed, Yan Meng +3
Diversity is an essential metric for evaluating the creativity of outputs generated by language models. Temperature-based sampling is a common strategy to increase diversity. Howev…
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…