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Erik-Lān Do Dinh
Erik-Lān Do Dinh
doctoral researcher, Ubiquitous Knowledge Processing (UKP) Lab, Technische Universität Darmstadt
Verified email at ukp.informatik.tu-darmstadt.de
Title
Cited by
Cited by
Year
Token-level metaphor detection using neural networks
EL Do Dinh, I Gurevych
Proceedings of the Fourth Workshop on Metaphor in NLP, 28-33, 2016
542016
Still not there? Comparing traditional sequence-to-sequence models to encoder-decoder neural networks on monotone string translation tasks
C Schnober, S Eger, ELD Dinh, I Gurevych
arXiv preprint arXiv:1610.07796, 2016
402016
Weeding out conventionalized metaphors: A corpus of novel metaphor annotations
EL Do Dinh, H Wieland, I Gurevych
Proceedings of the 2018 conference on empirical methods in natural language …, 2018
152018
Predicting humorousness and metaphor novelty with Gaussian process preference learning
E Simpson, EL Do Dinh, T Miller, I Gurevych
Proceedings of the 57th Annual Meeting of the Association for Computational …, 2019
142019
Killing four birds with two stones: Multi-task learning for non-literal language detection
EL Do Dinh, S Eger, I Gurevych
Proceedings of the 27th International Conference on Computational …, 2018
102018
Eelection at semeval-2017 task 10: Ensemble of neural learners for keyphrase classification
S Eger, ELD Dinh, I Kuznetsov, M Kiaeeha, I Gurevych
arXiv preprint arXiv:1704.02215, 2017
82017
A ‘wind of change’—shaping public opinion of the Arab Spring using metaphors
A Nśńez, M Gerloff, EL Do Dinh, A Rapp, P Gehring, I Gurevych
Digital Scholarship in the Humanities 34 (Supplement_1), i142-i149, 2019
32019
OFAI-UKP at HAHA@ IberLEF2019: Predicting the Humorousness of Tweets Using Gaussian Process Preference Learning.
T Miller, EL Do Dinh, E Simpson, I Gurevych
IberLEF@ SEPLN, 180-190, 2019
32019
One size fits all? A simple LSTM for non-literal token and construction-level classification
EL Do Dinh, S Eger, I Gurevych
Proceedings of the second joint SIGHUM workshop on computational linguistics …, 2018
32018
Predicting the humorousness of tweets using gaussian process preference learning
T Miller, ELD Dinh, E Simpson, I Gurevych
arXiv preprint arXiv:2008.00853, 2020
22020
In-tool Learning for Selective Manual Annotation in Large Corpora
EL Do Dinh, RE de Castilho, I Gurevych
Proceedings of ACL-IJCNLP 2015 System Demonstrations, 13-18, 2015
12015
Identificando el humor de tuits utilizando el aprendizaje de preferencias basado en procesos gaussianos
T Miller, I Gurevich, E Simpson, EL Do Dinh
Procesamiento del lenguaje natural, 37-44, 2020
2020
Filter and Annotate: Towards Automatic Identification of Genuine Metaphoricity
EL Do Dinh, I Gurevych, P Gehring
2018 IEEE 14th International Conference on e-Science (e-Science), 308-309, 2018
2018
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