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cs.CL2024
Investigating the potential of Sparse Mixtures-of-Experts for multi-domain neural machine translation
Nadezhda Chirkova, Vassilina Nikoulina, Jean-Luc Meunier +1
We focus on multi-domain Neural Machine Translation, with the goal of developing efficient models which can handle data from various domains seen during training and are robust to…
cs.CL2024
Understanding and Mitigating Language Confusion in LLMs
Kelly Marchisio, Wei-Yin Ko, Alexandre Bérard +2
We investigate a surprising limitation of LLMs: their inability to consistently generate text in a user's desired language. We create the Language Confusion Benchmark (LCB) to eval…