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Køpsala: Transition-Based Graph Parsing via Efficient Training and
  Effective Encoding

Køpsala: Transition-Based Graph Parsing via Efficient Training and Effective Encoding

25 May 2020
Daniel Hershcovich
Miryam de Lhoneux
Artur Kulmizev
E. Pejhan
Joakim Nivre
ArXivPDFHTML

Papers citing "Køpsala: Transition-Based Graph Parsing via Efficient Training and Effective Encoding"

3 / 3 papers shown
Title
TGIF: Tree-Graph Integrated-Format Parser for Enhanced UD with Two-Stage
  Generic- to Individual-Language Finetuning
TGIF: Tree-Graph Integrated-Format Parser for Enhanced UD with Two-Stage Generic- to Individual-Language Finetuning
Tianze Shi
Lillian Lee
30
7
0
14 Jul 2021
HUJI-KU at MRP~2020: Two Transition-based Neural Parsers
HUJI-KU at MRP~2020: Two Transition-based Neural Parsers
Ofir Arviv
Ruixiang Cui
Daniel Hershcovich
42
10
0
12 Oct 2020
Stanza: A Python Natural Language Processing Toolkit for Many Human
  Languages
Stanza: A Python Natural Language Processing Toolkit for Many Human Languages
Peng Qi
Yuhao Zhang
Yuhui Zhang
Jason Bolton
Christopher D. Manning
AI4TS
213
1,656
0
16 Mar 2020
1