Spremljaj
Katharina von der Wense
Katharina von der Wense
Druga imenaKatharina Kann
Johannes Gutenberg University Mainz & University of Colorado Boulder
Preverjeni e-poštni naslov na colorado.edu - Domača stran
Naslov
Navedeno
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Leto
Comparative study of CNN and RNN for natural language processing
W Yin, K Kann, M Yu, H Schütze
arXiv preprint arXiv:1702.01923, 2017
15702017
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
3012020
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
1552018
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
1192016
Single-model encoder-decoder with explicit morphological representation for reinflection
K Kann, H Schütze
arXiv preprint arXiv:1606.00589, 2016
992016
Sentence-level fluency evaluation: References help, but can be spared!
K Kann, S Rothe, K Filippova
arXiv preprint arXiv:1809.08731, 2018
892018
AmericasNLI: Evaluating zero-shot natural language understanding of pretrained multilingual models in truly low-resource languages
A Ebrahimi, M Mager, A Oncevay, V Chaudhary, L Chiruzzo, A Fan, ...
arXiv preprint arXiv:2104.08726, 2021
882021
Findings of the AmericasNLP 2021 shared task on open machine translation for indigenous languages of the Americas
M Mager, A Oncevay, A Ebrahimi, J Ortega, AR Gonzales, A Fan, ...
Proceedings of the First Workshop on Natural Language Processing for …, 2021
812021
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
772020
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
702018
Training data augmentation for low-resource morphological inflection
T Bergmanis, K Kann, H Schütze, S Goldwater
CoNLL SIGMORPHON 2017 Shared Task: Universal Morphological Reinflection, 31-39, 2017
632017
How to adapt your pretrained multilingual model to 1600 languages
A Ebrahimi, K Kann
arXiv preprint arXiv:2106.02124, 2021
602021
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
552019
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
552016
Towards realistic practices in low-resource natural language processing: The development set
K Kann, K Cho, SR Bowman
arXiv preprint arXiv:1909.01522, 2019
532019
Verb argument structure alternations in word and sentence embeddings
K Kann, A Warstadt, A Williams, SR Bowman
arXiv preprint arXiv:1811.10773, 2018
532018
Probing for semantic classes: Diagnosing the meaning content of word embeddings
Y Yaghoobzadeh, K Kann, TJ Hazen, E Agirre, H Schütze
arXiv preprint arXiv:1906.03608, 2019
452019
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
452017
CLiMP: A benchmark for Chinese language model evaluation
B Xiang, C Yang, Y Li, A Warstadt, K Kann
arXiv preprint arXiv:2101.11131, 2021
442021
One-shot neural cross-lingual transfer for paradigm completion
K Kann, R Cotterell, H Schütze
arXiv preprint arXiv:1704.00052, 2017
442017
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