6 papers
The Sensitivity of Language Models and Humans to Winograd Schema Perturbations
Mostafa Abdou, Vinit Ravishankar, Maria Barrett +3
Large-scale pretrained language models are the major driving force behind recent improvements in performance on the Winograd Schema Challenge, a widely employed test of common sens…
Do Neural Language Models Show Preferences for Syntactic Formalisms?
Artur Kulmizev, Vinit Ravishankar, Mostafa Abdou +1
Recent work on the interpretability of deep neural language models has concluded that many properties of natural language syntax are encoded in their representational spaces. Howev…
Compositional Generalization in Image Captioning
Mitja Nikolaus, Mostafa Abdou, Matthew Lamm +2
Image captioning models are usually evaluated on their ability to describe a held-out set of images, not on their ability to generalize to unseen concepts. We study the problem of…
Higher-order Comparisons of Sentence Encoder Representations
Mostafa Abdou, Artur Kulmizev, Felix Hill +2
Representational Similarity Analysis (RSA) is a technique developed by neuroscientists for comparing activity patterns of different measurement modalities (e.g., fMRI, electrophysi…
X-WikiRE: A Large, Multilingual Resource for Relation Extraction as Machine Comprehension
Mostafa Abdou, Cezar Sas, Rahul Aralikatte +2
Although the vast majority of knowledge bases KBs are heavily biased towards English, Wikipedias do cover very different topics in different languages. Exploiting this, we introduc…
Better, Faster, Stronger Sequence Tagging Constituent Parsers
David Vilares, Mostafa Abdou, Anders Søgaard
Sequence tagging models for constituent parsing are faster, but less accurate than other types of parsers. In this work, we address the following weaknesses of such constituent par…