On April 12, 2023, Daoxin Li, advised by Charles Yang, successfully defended her PhD proposal, entitled "Distributional learning of syntactic generalizations” (abstract below). His proposal committee included Julie Anne Legate and Kathryn Schuler and was chaired by Marlyse Baptista
Abstract: During language acquisition, children are tasked with the challenge of determining which words can appear in which syntactic constructions. This has been long recognized as a serious learnability problem. On one hand, there are productive generalizations that children must learn. On the other, language is known for its arbitrariness, so children also need to decide when not to generalize and memorize the exceptions. Finally, the picture is further complicated by the lack of negative evidence of what sentences are ungrammatical in a language. In this dissertation, by applying a threshold-based generalization learning model The Tolerance/Sufficiency Principle, I provide novel approaches to the acquisition of a range of syntactic generalizations across languages, including verb argument structure and recursive structures. Ultimately, this dissertation aims to contribute quantitatively rigorous and psychologically real solutions to the well-known learning problem, offering new perspectives for the mechanisms of learning generalizations.