← Back to papers
2023 CONLL CoNLL 2023

Increasing The Performance of Cognitively Inspired Data-Efficient Language Models via Implicit Structure Building

Authors

Omar Momen , David Arps , Laura Kallmeyer
Download PDF

Related papers

ToMChallenges: A Principle-Guided Dataset and Diverse Evaluation Tasks for Exploring Theory of Mind 2023
On the Effects of Structural Modeling for Neural Semantic Parsing 2023
ArchBERT: Bi-Modal Understanding of Neural Architectures and Natural Languages 2023
A Comparative Study on Textual Saliency of Styles from Eye Tracking, Annotations, and Language Models 2023
PROPRES: Investigating the Projectivity of Presupposition with Various Triggers and Environments 2023