2 citations · 2 across the 4 of their papers we have counts for
3 papers · 1 filter
Typological Alignment of Stack-Based Language Models on Mildly Context-Sensitive Artificial Languages
Nadine El-Naggar, Tatsuki Kuribayashi, Ted Briscoe
Some properties of languages, e.g., subject-object-verb (SOV) word order, are more prevalent than others among the thousands of attested natural languages (NLs). Such typological c…
What Kind of Language is Easy to Language-Model Under Curriculum Learning?
Nadine El-Naggar, Tatsuki Kuribayashi, Ted Briscoe
Many of the thousands of attested languages share common configurations of features, creating a spectrum from typologically very rare (e.g., object-verb-subject word order) or impo…
Which Word Orders Facilitate Length Generalization in LMs? An Investigation with GCG-Based Artificial Languages
Nadine El-Naggar, Tatsuki Kuribayashi, Ted Briscoe
Whether language models (LMs) have inductive biases that favor typologically frequent grammatical properties over rare, implausible ones has been investigated, typically using arti…