1 citations · 1 across the 1 of their papers we have counts for
5 papers
Uppsala NLP at SemEval-2021 Task 2: Multilingual Language Models for Fine-tuning and Feature Extraction in Word-in-Context Disambiguation
Huiling You, Xingran Zhu, Sara Stymne
We describe the Uppsala NLP submission to SemEval-2021 Task 2 on multilingual and cross-lingual word-in-context disambiguation. We explore the usefulness of three pre-trained multi…
What Should/Do/Can LSTMs Learn When Parsing Auxiliary Verb Constructions?
Miryam de Lhoneux, Sara Stymne, Joakim Nivre
There is a growing interest in investigating what neural NLP models learn about language. A prominent open question is the question of whether or not it is necessary to model hiera…
82 Treebanks, 34 Models: Universal Dependency Parsing with Multi-Treebank Models
Aaron Smith, Bernd Bohnet, Miryam de Lhoneux +3
We present the Uppsala system for the CoNLL 2018 Shared Task on universal dependency parsing. Our system is a pipeline consisting of three components: the first performs joint word…
An Investigation of the Interactions Between Pre-Trained Word Embeddings, Character Models and POS Tags in Dependency Parsing
Aaron Smith, Miryam de Lhoneux, Sara Stymne +1
We provide a comprehensive analysis of the interactions between pre-trained word embeddings, character models and POS tags in a transition-based dependency parser. While previous s…
Parser Training with Heterogeneous Treebanks
Sara Stymne, Miryam de Lhoneux, Aaron Smith +1
How to make the most of multiple heterogeneous treebanks when training a monolingual dependency parser is an open question. We start by investigating previously suggested, but litt…