activity
20192021
most citedSequence Labeling Parsing by Learning Across Representations

17 citations · 24 across the 6 of their papers we have counts for

collaborators

8 papers

cs.CL2021

Not All Linearizations Are Equally Data-Hungry in Sequence Labeling Parsing

Alberto Muñoz-Ortiz, Michalina Strzyz, David Vilares

Different linearizations have been proposed to cast dependency parsing as sequence labeling and solve the task as: (i) a head selection problem, (ii) finding a representation of th…

cs.CL2020

Bracketing Encodings for 2-Planar Dependency Parsing

Michalina Strzyz, David Vilares, Carlos Gómez-Rodríguez

We present a bracketing-based encoding that can be used to represent any 2-planar dependency tree over a sentence of length n as a sequence of n labels, hence providing almost tota…

cs.CL2020

A Unifying Theory of Transition-based and Sequence Labeling Parsing

Carlos Gómez-Rodríguez, Michalina Strzyz, David Vilares

We define a mapping from transition-based parsing algorithms that read sentences from left to right to sequence labeling encodings of syntactic trees. This not only establishes a t…

cs.CL2020★ 6 cited

Parsing as Pretraining

David Vilares, Michalina Strzyz, Anders Søgaard +1

Recent analyses suggest that encoders pretrained for language modeling capture certain morpho-syntactic structure. However, probing frameworks for word vectors still do not report…

cs.CL2019

Towards Making a Dependency Parser See

Michalina Strzyz, David Vilares, Carlos Gómez-Rodríguez

We explore whether it is possible to leverage eye-tracking data in an RNN dependency parser (for English) when such information is only available during training, i.e., no aggregat…

cs.CL2019★ 17 cited

Sequence Labeling Parsing by Learning Across Representations

Michalina Strzyz, David Vilares, Carlos Gómez-Rodríguez

We use parsing as sequence labeling as a common framework to learn across constituency and dependency syntactic abstractions. To do so, we cast the problem as multitask learning (M…

cs.CL2019

Speeding Up Natural Language Parsing by Reusing Partial Results

Michalina Strzyz, Carlos Gómez-Rodríguez

This paper proposes a novel technique that applies case-based reasoning in order to generate templates for reusable parse tree fragments, based on PoS tags of bigrams and trigrams…

cs.CL2019★ 1 cited

Viable Dependency Parsing as Sequence Labeling

Michalina Strzyz, David Vilares, Carlos Gómez-Rodríguez

We recast dependency parsing as a sequence labeling problem, exploring several encodings of dependency trees as labels. While dependency parsing by means of sequence labeling had b…