1 citations · 1 across the 6 of their papers we have counts for
7 papers
From Parallels to Divergence: Language Models' Learning of Action Nominal Constructions
Iskar Deng, Shane Steinert-Threlkeld
Action nominal constructions (ANCs) express events in nominal form, with their argument marking following patterns found in clauses or ordinary noun phrases. In this paper, we inve…
Language Models Generalize to Human-like Word Order Preferences
Amanda Popadich, Shane Steinert-Threlkeld
A central question in language acquisition is whether linguistic biases can emerge from general learning mechanisms operating over underdetermined input. Artificial Language Learni…
Exposure is Optional: Learning Unlike Coordination in Language Models
Jiamu Luo, Shane Steinert-Threlkeld
Coordination, a fundamental linguistic structure, remains a subject of intense debate, and its exact nature continues to elude theoretical linguistics. A common view holds that onl…
Differences in Typological Alignment in Language Models' Treatment of Differential Argument Marking
Iskar Deng, Nathalia Xu, Shane Steinert-Threlkeld
Recent work has shown that language models (LMs) trained on synthetic corpora can exhibit typological preferences that resemble cross-linguistic regularities in human languages, pa…
Minimization of Boolean Complexity in In-Context Concept Learning
Leroy Z. Wang, R. Thomas McCoy, Shane Steinert-Threlkeld
What factors contribute to the relative success and corresponding difficulties of in-context learning for Large Language Models (LLMs)? Drawing on insights from the literature on h…
Targeted Multilingual Adaptation for Low-resource Language Families
C. M. Downey, Terra Blevins, Dhwani Serai +2
The "massively-multilingual" training of multilingual models is known to limit their utility in any one language, and they perform particularly poorly on low-resource languages. Ho…
Filtered Corpus Training (FiCT) Shows that Language Models can Generalize from Indirect Evidence
Abhinav Patil, Jaap Jumelet, Yu Ying Chiu +5
This paper introduces Filtered Corpus Training, a method that trains language models (LMs) on corpora with certain linguistic constructions filtered out from the training data, and…