6 citations · 6 across the 4 of their papers we have counts for
4 papers · 1 filter
How-to Guides for Specific Audiences: A Corpus and Initial Findings
Nicola Fanton, Agnieszka Falenska, Michael Roth
Instructional texts for specific target groups should ideally take into account the prior knowledge and needs of the readers in order to guide them efficiently to their desired goa…
The (Non-)Utility of Structural Features in BiLSTM-based Dependency Parsers
Agnieszka Falenska, Jonas Kuhn
Classical non-neural dependency parsers put considerable effort on the design of feature functions. Especially, they benefit from information coming from structural features, such…
IMS at the PolEval 2018: A Bulky Ensemble Depedency Parser meets 12 Simple Rules for Predicting Enhanced Dependencies in Polish
Agnieszka Falenska, Anders Björkelund, Xiang Yu +1
This paper presents the IMS contribution to the PolEval 2018 Shared Task. We submitted systems for both of the Subtasks of Task 1. In Subtask (A), which was about dependency parsin…
A General-Purpose Tagger with Convolutional Neural Networks
Xiang Yu, Agnieszka Faleńska, Ngoc Thang Vu
We present a general-purpose tagger based on convolutional neural networks (CNN), used for both composing word vectors and encoding context information. The CNN tagger is robust ac…