24 citations · 75 across the 22 of their papers we have counts for
3 papers · 1 filter
On the Compositional Generalization Gap of In-Context Learning
Arian Hosseini, Ankit Vani, Dzmitry Bahdanau +2
Pretrained large generative language models have shown great performance on many tasks, but exhibit low compositional generalization abilities. Scaling such models has been shown t…
Understanding by Understanding Not: Modeling Negation in Language Models
Arian Hosseini, Siva Reddy, Dzmitry Bahdanau +3
Negation is a core construction in natural language. Despite being very successful on many tasks, state-of-the-art pre-trained language models often handle negation incorrectly. To…
Explicitly Modeling Syntax in Language Models with Incremental Parsing and a Dynamic Oracle
Yikang Shen, Shawn Tan, Alessandro Sordoni +2
Syntax is fundamental to our thinking about language. Failing to capture the structure of input language could lead to generalization problems and over-parametrization. In the pres…