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Found 13 papers, 0 papers with code
Lexical Resources for Low-Resource PoS Tagging in Neural Times
More and more evidence is appearing that integrating symbolic lexical knowledge into neural models aids learning.
At a Glance: The Impact of Gaze Aggregation Views on Syntactic Tagging
Hence, caution is warranted when using gaze data as signal for NLP, as no single view is robust over tasks, modeling choice and gaze corpus.
The Best of Both Worlds: Lexical Resources To Improve Low-Resource Part-of-Speech Tagging
In natural language processing, the deep learning revolution has shifted the focus from conventional hand-crafted symbolic representations to dense inputs, which are adequate representations learned automatically from corpora.
Grotoco@SLAM: Second Language Acquisition Modeling with Simple Features, Learners and Task-wise Models
We present our submission to the 2018 Duolingo Shared Task on Second Language Acquisition Modeling (SLAM).
Predicting misreadings from gaze in children with reading difficulties
We present the first work on predicting reading mistakes in children with reading difficulties based on eye-tracking data from real-world reading teaching.
Improving sentence compression by learning to predict gaze
We show how eye-tracking corpora can be used to improve sentence compression models, presenting a novel multi-task learning algorithm based on multi-layer LSTMs.
Ranked #5 on
Sentence Compression
on Google Dataset
DSim, a Danish Parallel Corpus for Text Simplification
We compare DSim to different examples of monolingual parallel corpora, and we argue that this corpus is a promising basis for future development of automatic data-driven text simplification systems in Danish.
