19 citations · 19 across the 3 of their papers we have counts for
13 papers
Does injecting linguistic structure into language models lead to better alignment with brain recordings?
Mostafa Abdou, Ana Valeria Gonzalez, Mariya Toneva +2
Neuroscientists evaluate deep neural networks for natural language processing as possible candidate models for how language is processed in the brain. These models are often traine…
Comparison by Conversion: Reverse-Engineering UCCA from Syntax and Lexical Semantics
Daniel Hershcovich, Nathan Schneider, Dotan Dvir +3
Building robust natural language understanding systems will require a clear characterization of whether and how various linguistic meaning representations complement each other. To…
HUJI-KU at MRP~2020: Two Transition-based Neural Parsers
Ofir Arviv, Ruixiang Cui, Daniel Hershcovich
This paper describes the HUJI-KU system submission to the shared task on Cross-Framework Meaning Representation Parsing (MRP) at the 2020 Conference for Computational Language Lear…
Joint Semantic Analysis with Document-Level Cross-Task Coherence Rewards
Rahul Aralikatte, Mostafa Abdou, Heather Lent +2
Coreference resolution and semantic role labeling are NLP tasks that capture different aspects of semantics, indicating respectively, which expressions refer to the same entity, an…
Køpsala: Transition-Based Graph Parsing via Efficient Training and Effective Encoding
Daniel Hershcovich, Miryam de Lhoneux, Artur Kulmizev +2
We present Køpsala, the Copenhagen-Uppsala system for the Enhanced Universal Dependencies Shared Task at IWPT 2020. Our system is a pipeline consisting of off-the-shelf models for…
Refining Implicit Argument Annotation for UCCA
Ruixiang Cui, Daniel Hershcovich
Predicate-argument structure analysis is a central component in meaning representations of text. The fact that some arguments are not explicitly mentioned in a sentence gives rise…