Zobrazeno 1 - 7
of 7
pro vyhledávání: '"Schenk, Niko"'
Autor:
Bansal, Rachit, Choudhary, Himanshu, Punia, Ravneet, Schenk, Niko, Dahl, Jacob L, Pagé-Perron, Émilie
Despite the recent advancements of attention-based deep learning architectures across a majority of Natural Language Processing tasks, their application remains limited in a low-resource setting because of a lack of pre-trained models for such langua
Externí odkaz:
http://arxiv.org/abs/2105.14515
We introduce an attention-based Bi-LSTM for Chinese implicit discourse relations and demonstrate that modeling argument pairs as a joint sequence can outperform word order-agnostic approaches. Our model benefits from a partial sampling scheme and is
Externí odkaz:
http://arxiv.org/abs/1704.08092
Linguistic Linked Open Data (LLOD) is a flourishing line of research in the language resource community, so far mostly adopted for selected aspects of linguistics, natural language processing and the semantic web, as well as for practical application
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3341::5236d831c299f58e430d90f823d44356
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/104100
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/104100
This paper describes our contribution to the Third Shared Task on Translation Inference across Dictionaries (TIAD-2020). We describe an approach on translation inference based on symbolic methods, the propagation of concepts over a graph of interconn
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od______3341::69e821034a6a0eea59de790df0a7ec01
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/104026
https://opus.bibliothek.uni-augsburg.de/opus4/frontdoor/index/index/docId/104026
Autor:
Schenk, Niko
Human readers have the ability to infer knowledge from text, even if that particular information is not explicitly stated. In this thesis, we address the phenomena of text-level implicit information and outline novel automated methods for its recover
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=od_______603::8a8ccfd25945f6945992088b4346d2fd
http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/50983
http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/50983
Autor:
Chiarcos, Christian1 chiarcos@informatik.uni-frankfurt.de, Khait, Ilya1 khait@informatik.uni-frankfurt.de, Pagé-Perron, Émilie2,3 bill.mcgrath@mail.utoronto.ca, Schenk, Niko1 schenk@informatik.uni-frankfurt.de, Jayanth2, Fäth, Christian1 faeth@informatik.uni-frankfurt.de, Steuer, Julius1 steuer@informatik.uni-frankfurt.de, Mcgrath, William3 jinyan.wang@mail.utoronto.ca, Wang, Jinyan3
Publikováno v:
Information (2078-2489). Nov2018, Vol. 9 Issue 11, p290. 1p.