125 citations · 584 across the 45 of their papers we have counts for
4 papers · 1 filter
Do Language Models' Words Refer?
Matthew Mandelkern, Tal Linzen
What do language models (LMs) do with language? Everyone agrees that they can produce sequences of (mostly) coherent strings of English. But do those sentences mean something, or a…
Language Models Can Learn Exceptions to Syntactic Rules
Cara Su-Yi Leong, Tal Linzen
Artificial neural networks can generalize productively to novel contexts. Can they also learn exceptions to those productive rules? We explore this question using the case of restr…
How to Plant Trees in Language Models: Data and Architectural Effects on the Emergence of Syntactic Inductive Biases
Aaron Mueller, Tal Linzen
Accurate syntactic representations are essential for robust generalization in natural language. Recent work has found that pre-training can teach language models to rely on hierarc…
How poor is the stimulus? Evaluating hierarchical generalization in neural networks trained on child-directed speech
Aditya Yedetore, Tal Linzen, Robert Frank +1
When acquiring syntax, children consistently choose hierarchical rules over competing non-hierarchical possibilities. Is this preference due to a learning bias for hierarchical str…