3
presentations
3
number of views
SHORT BIO
My research explores the emergence of language universals using neural agent simulations. Currently, I’m focusing on the word order/case-marking trade-off in natural languages, which is one of the most well-known language universals. I have developed a cutting-edge framework called NeLLCom, which stands for Neural-agent Language Learning and Communication. Basic model training procedures such as supervised learning and rewards fine-tuning based on communicative success are implemented there. Taking inspiration from Language Evolution research, NeLLCom also carries out various other learning paradigms, e.g. iterated learning and group communication.
Presentations
Communication Drives the Emergence of Language Universals in Neural Agents: Evidence from the Word-order/Case-marking Trade-off" | VIDEO
Yuchen Lian and 2 other authors
The Effect of Efficient Messaging and Input Variability on Neural-Agent Iterated Language Learning
Yuchen Lian and 2 other authors
The importance of communicative success for simulating the emergence of a Word Order/Case Marking trade-off with Neural Agents
Yuchen Lian and 2 other authors