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Start Over Contributor Grantová agentura České republiky@@GX20-16819X@@LUSyD – Language Understanding: from Syntax to Discourse@@nationalFunds@@ Language Polish Publisher Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL) Rights http://creativecommons.org/licenses/by-nc-sa/4.0/

1. CorPipe 23 multilingual CorefUD 1.1 model (corpipe23-corefud1.1-231206)

Creator:
Straka, Milan
Publisher:
Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:
tool and toolService
Subject:
coreference resolution, CorPipe, and CorefUD
Language:
Catalan, Czech, German, English, Spanish, French, Hungarian, Lithuanian, Norwegian Bokmål, Norwegian Nynorsk, Polish, Russian, and Turkish
Description:
The `corpipe23-corefud1.1-231206` is a `mT5-large`-based multilingual model for coreference resolution usable in CorPipe 23 (https://github.com/ufal/crac2023-corpipe). It is released under the CC BY-NC-SA 4.0 license. The model is language agnostic (no _corpus id_ on input), so it can be used to predict coreference in any `mT5` language (for zero-shot evaluation, see the paper). However, note that the empty nodes must be present already on input, they are not predicted (the same settings as in the CRAC23 shared task).
Rights:
Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB

2. CUBBITT Translation Models (en-pl) (v1.0)

Creator:
Popel, Martin, Tomková, Markéta, Tomek, Jakub, Kaiser, Łukasz, Uszkoreit, Jakob, Bojar, Ondřej, and Žabokrtský, Zdeněk
Publisher:
Charles University, Faculty of Mathematics and Physics, Institute of Formal and Applied Linguistics (UFAL)
Type:
tool and toolService
Subject:
machine translation, neural machine translation, transformer, and cubbitt
Language:
English and Polish
Description:
CUBBITT En-Pl translation models, exported via TensorFlow Serving, available in the Lindat translation service (https://lindat.mff.cuni.cz/services/translation/). Models are compatible with Tensor2tensor version 1.6.6. For details about the model training (data, model hyper-parameters), please contact the archive maintainer. Evaluation on newstest2020 (BLEU): en->pl: 12.3 pl->en: 20.0 (Evaluated using multeval: https://github.com/jhclark/multeval)
Rights:
Creative Commons - Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0), http://creativecommons.org/licenses/by-nc-sa/4.0/, and PUB