6 citations · 7 across the 4 of their papers we have counts for
8 papers
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…
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…
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…
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…
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…
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…