Improving sentence compression by learning to predict gaze
April 12, 2016 Β· Declared Dead Β· π North American Chapter of the Association for Computational Linguistics
"No code URL or promise found in abstract"
Evidence collected by the PWNC Scanner
Authors
Sigrid Klerke, Yoav Goldberg, Anders SΓΈgaard
arXiv ID
1604.03357
Category
cs.CL: Computation & Language
Citations
129
Venue
North American Chapter of the Association for Computational Linguistics
Last Checked
2 months ago
Abstract
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. We obtain performance competitive with or better than state-of-the-art approaches.
Community Contributions
Found the code? Know the venue? Think something is wrong? Let us know!
π Similar Papers
In the same crypt β Computation & Language
π
π
Old Age
π
π
Old Age
BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding
R.I.P.
π»
Ghosted
Language Models are Few-Shot Learners
R.I.P.
π»
Ghosted
RoBERTa: A Robustly Optimized BERT Pretraining Approach
R.I.P.
π»
Ghosted
BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension
R.I.P.
π»
Ghosted
Deep contextualized word representations
Died the same way β π» Ghosted
R.I.P.
π»
Ghosted
PyTorch: An Imperative Style, High-Performance Deep Learning Library
R.I.P.
π»
Ghosted
XGBoost: A Scalable Tree Boosting System
R.I.P.
π»
Ghosted
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
R.I.P.
π»
Ghosted