12 citations · 16 across the 4 of their papers we have counts for
4 papers
Tokenization and Morphology in Multilingual Language Models: A Comparative Analysis of mT5 and ByT5
Thao Anh Dang, Limor Raviv, Lukas Galke
Morphology is a crucial factor for multilingual language modeling as it poses direct challenges for tokenization. Here, we seek to understand how tokenization influences the morpho…
Learning and communication pressures in neural networks: Lessons from emergent communication
Lukas Galke, Limor Raviv
Finding and facilitating commonalities between the linguistic behaviors of large language models and humans could lead to major breakthroughs in our understanding of the acquisitio…
What makes a language easy to deep-learn? Deep neural networks and humans similarly benefit from compositional structure
Lukas Galke, Yoav Ram, Limor Raviv
Deep neural networks drive the success of natural language processing. A fundamental property of language is its compositional structure, allowing humans to systematically produce…
Emergent Communication for Understanding Human Language Evolution: What's Missing?
Lukas Galke, Yoav Ram, Limor Raviv
Emergent communication protocols among humans and artificial neural network agents do not yet share the same properties and show some critical mismatches in results. We describe th…