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cs.IR2024★ 2 cited
Creating a Taxonomy for Retrieval Augmented Generation Applications
Irina Nikishina, Özge Sevgili, Mahei Manhai Li +2
In this research, we develop a taxonomy to conceptualize a comprehensive overview of the constituting characteristics that define retrieval augmented generation (RAG) applications,…
cs.CL2024
Low-Resource Machine Translation through the Lens of Personalized Federated Learning
Viktor Moskvoretskii, Nazarii Tupitsa, Chris Biemann +3
We present a new approach called MeritOpt based on the Personalized Federated Learning algorithm MeritFed that can be applied to Natural Language Tasks with heterogeneous data. We…