Katharina Kann
Title
Cited by
Cited by
Year
Comparative study of CNN and RNN for natural language processing
W Yin, K Kann, M Yu, H Schütze
arXiv preprint arXiv:1702.01923, 2017
6562017
The CoNLL--SIGMORPHON 2018 Shared Task: Universal Morphological Reinflection
R Cotterell, C Kirov, J Sylak-Glassman, G Walther, E Vylomova, ...
arXiv preprint arXiv:1810.07125, 2018
982018
MED: The LMU system for the SIGMORPHON 2016 shared task on morphological reinflection
K Kann, H Schütze
Proceedings of the 14th SIGMORPHON Workshop on Computational Research in …, 2016
942016
Single-model encoder-decoder with explicit morphological representation for reinflection
K Kann, H Schütze
arXiv preprint arXiv:1606.00589, 2016
742016
Intermediate-task transfer learning with pretrained models for natural language understanding: When and why does it work?
Y Pruksachatkun, J Phang, H Liu, PM Htut, X Zhang, RY Pang, C Vania, ...
arXiv preprint arXiv:2005.00628, 2020
702020
Training data augmentation for low-resource morphological inflection
T Bergmanis, K Kann, H Schütze, S Goldwater
Proceedings of the CoNLL SIGMORPHON 2017 Shared Task: Universal …, 2017
462017
Comparative study of CNN and RNN for natural language processing. arXiv 2017
W Yin, K Kann, M Yu, H Schütze
arXiv preprint arXiv:1702.01923, 0
41
One-shot neural cross-lingual transfer for paradigm completion
K Kann, R Cotterell, H Schütze
arXiv preprint arXiv:1704.00052, 2017
382017
Fortification of neural morphological segmentation models for polysynthetic minimal-resource languages
K Kann, M Mager, I Meza-Ruiz, H Schütze
arXiv preprint arXiv:1804.06024, 2018
352018
Neural morphological analysis: Encoding-decoding canonical segments
K Kann, R Cotterell, H Schütze
Proceedings of the 2016 conference on empirical methods in natural language …, 2016
342016
Sentence-Level Fluency Evaluation: References Help, But Can Be Spared!
K Kann, S Rothe, K Filippova
arXiv preprint arXiv:1809.08731, 2018
322018
Neural multi-source morphological reinflection
K Kann, R Cotterell, H Schütze
arXiv preprint arXiv:1612.06027, 2016
322016
jiant 1.2: A software toolkit for research on general-purpose text understanding models
A Wang, IF Tenney, Y Pruksachatkun, K Yu, J Hula, P Xia, R Pappagari, ...
Note: http://jiant. info/Cited by: footnote 4, 2019
302019
English Intermediate-Task Training Improves Zero-Shot Cross-Lingual Transfer Too
J Phang, PM Htut, Y Pruksachatkun, H Liu, C Vania, K Kann, I Calixto, ...
AACL 2020, 2020
292020
Comparative study of CNN and RNN for natural language processing (2017)
W Yin, K Kann, M Yu, H Schütze
arXiv preprint arXiv:1702.01923, 2017
262017
The LMU system for the CoNLL-SIGMORPHON 2017 shared task on universal morphological reinflection
K Kann, H Schütze
Proceedings of the CoNLL SIGMORPHON 2017 Shared Task: Universal …, 2017
242017
Verb argument structure alternations in word and sentence embeddings
K Kann, A Warstadt, A Williams, SR Bowman
arXiv preprint arXiv:1811.10773, 2018
212018
Character-level supervision for low-resource POS tagging
K Kann, J Bjerva, I Augenstein, B Plank, A Søgaard
Proceedings of the Workshop on Deep Learning Approaches for Low-Resource NLP …, 2018
202018
The SIGMORPHON 2020 Shared Task on Unsupervised Morphological Paradigm Completion
K Kann, AD McCarthy, G Nicolai, M Hulden
SIGMORPHON 2020, 2020
18*2020
Towards realistic practices in low-resource natural language processing: the development set
K Kann, K Cho, SR Bowman
arXiv preprint arXiv:1909.01522, 2019
182019
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