31 to 40 of 185 Results
Nov 13, 2023 -
Head Selection Parsers and LSTM Labelers
Gzip Archive - 63.1 MB -
MD5: 528b7723f604878c239070e73509809d
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Nov 13, 2023 -
Head Selection Parsers and LSTM Labelers
Gzip Archive - 36.7 MB -
MD5: 72a03233b3e1cbfbc4420327a70d7f9a
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Nov 13, 2023 -
Head Selection Parsers and LSTM Labelers
Gzip Archive - 68.0 MB -
MD5: a362283a76428bb053c6f59a928b3a8d
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Nov 13, 2023 -
Head Selection Parsers and LSTM Labelers
Gzip Archive - 32.5 MB -
MD5: 2d06256605fad989aa18b00e46922463
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Nov 13, 2023 -
Head Selection Parsers and LSTM Labelers
Gzip Archive - 32.4 MB -
MD5: a7fa938e3000c7e0427ef3c2b3ec8d28
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Nov 13, 2023 - Neural Techniques for German Dependency Parsing
Do, Bich-Ngoc; Rehbein, Ines, 2023, "Neural Rerankers for Dependency Parsing", https://doi.org/10.11588/data/NNGPQZ, heiDATA, V1
This resource contains code for different types of neural rerankers (RCNN, RCNN-shared and GCN) from the paper: Do and Rehbein (2020). "Neural Reranking for Dependency Parsing: An Evaluation". We also include in this resource the pre-trained models of different rerankers on 3 lan... |
Nov 13, 2023 -
Neural Rerankers for Dependency Parsing
Gzip Archive - 64.5 MB -
MD5: c9066cb993f7f932b4dd3b2f57ab0df8
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Nov 13, 2023 -
Neural Rerankers for Dependency Parsing
Gzip Archive - 58.0 MB -
MD5: 271f2b6ad94a1b3a5b5c37db948d0b7d
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Nov 13, 2023 -
Neural Rerankers for Dependency Parsing
Gzip Archive - 72.6 MB -
MD5: 932ba4a18453cb66131e05b0a5296b59
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Nov 13, 2023 -
Neural Rerankers for Dependency Parsing
Gzip Archive - 36.5 MB -
MD5: fe026cd97d3f3853cf31bae9251fcbf5
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