2018
EMNLP
EMNLP 2018
Does Syntactic Knowledge in Multilingual Language Models Transfer Across Languages?
Abstract
AbstractRecent work has shown that neural models can be successfully trained on multiple languages simultaneously. We investigate whether such models learn to share and exploit common syntactic knowledge among the languages on which they are trained. This extended abstract presents our preliminary results.
❓
The Questioner
🌉
Interdisciplinary Bridge
— Artificial Intelligence and Deep Learning and Natural Language Processing
📈
Trend Setter
— Transfer Learning
🐣
Hot Topic Early Bird
— multilingual language model
🐝
Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio