4 papers
Massively Multilingual Joint Segmentation and Glossing
Michael Ginn, Lindia Tjuatja, Enora Rice +5
Automated interlinear gloss prediction with neural networks is a promising approach to accelerate language documentation efforts. However, while state-of-the-art models like GlossL…
Neural Induction of Finite-State Transducers
Michael Ginn, Alexis Palmer, Mans Hulden
Finite-State Transducers (FSTs) are effective models for string-to-string rewriting tasks, often providing the efficiency necessary for high-performance applications, but construct…
Speculative Decoding and the Curse of Multilinguality
Nirajan Paudel, Michael Ginn, Luc De Nardi +1
Speculative decoding is a popular technique for large language model (LLM) inference, enabling faster generation by drafting multiple tokens with a smaller draft model. However, th…
Is linguistically-motivated data augmentation worth it?
Ray Groshan, Michael Ginn, Alexis Palmer
Data augmentation, a widely-employed technique for addressing data scarcity, involves generating synthetic data examples which are then used to augment available training data. Res…