Limor Raviv

1. Tokenization and Morphology in Multilingual Language Models: A Comparative Analysis of mT5 and ByT5
   2024/10/15 by Thanh Diem Dang, Limor Raviv, Dang, Thao Anh +3 · 7 citations
   Computer Science · #Computation and Language (cs.CL) #FOS: Computer and information sciences #I.2.7 #Natural Language Processing Techniques
2. Emergent Communication for Understanding Human Language Evolution: What's Missing?
   2022/04/22 by Lukas Galke, Galke, Lukas, Yoav Ram +3 · 3 citations
   Computer Science · Social Sciences · #Computation and Language (cs.CL) #FOS: Computer and information sciences #I.2.7 #Language and cultural evolution #Machine Learning (cs.LG) #Natural Language Processing Techniques #Neural and Evolutionary Computing (cs.NE) #Speech and dialogue systems
3. What enables human language? A biocultural framework
   2025/11/20 by Inbal Arnon, Liran Carmel, Nicolas Claidière +7 · 2 voices · 7 citations
   Social Sciences · Biochemistry, Genetics and Molecular Biology · Psychology · #Language and cultural evolution #Animal Vocal Communication and Behavior #Categorization, perception, and language
4. Deep neural networks and humans both benefit from compositional language structure
   2024/12/30 by Lukas Galke, Yoav Ram, Limor Raviv · 1 voice · 3 citations
   Computer Science · Social Sciences · #Language and cultural evolution #Natural Language Processing Techniques #Topic Modeling
5. The ‘design features’ of language revisited
   2025/11/25 by Michael Pleyer, Marcus Perlman, Gary Lupyan +2 · 3 voices · 3 citations
   Social Sciences · Psychology · #Language and cultural evolution #Categorization, perception, and language #Language, Metaphor, and Cognition
6. Learning and communication pressures in neural networks: Lessons from emergent communication
   2024/11/04 by Lukas Galke, Limor Raviv · 1 citation
   Neuroscience · #Cognitive Science and Education Research #emergent communication #language acquisition #language evolution #large language models #learning biases #learning pressures #multi-agent systems #neural language models #neural networks