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2nd MSR@EMNLP 2019: Hong Kong, China
- Simon Mille, Anja Belz, Bernd Bohnet, Yvette Graham, Leo Wanner:
Proceedings of the 2nd Workshop on Multilingual Surface Realisation, MSR@EMNLP-IJCNLP 2019, Hong Kong, China, November 3, 2019. Association for Computational Linguistics 2019, ISBN 978-1-950737-76-5 - Simon Mille, Anja Belz
, Bernd Bohnet, Yvette Graham, Leo Wanner:
The Second Multilingual Surface Realisation Shared Task (SR'19): Overview and Evaluation Results. 1-17 - Wenchao Du, Alan W. Black:
Learning to Order Graph Elements with Application to Multilingual Surface Realization. 18-24 - William Dyer:
DepDist: Surface realization via regex and learned dependency-distance tolerance. 25-34 - Ádám Kovács
, Evelin Ács, Judit Ács, András Kornai, Gábor Recski
:
BME-UW at SRST-2019: Surface realization with Interpreted Regular Tree Grammars. 35-40 - Guy Lapalme:
Realizing Universal Dependencies Structures. 41-49 - Xiang Yu, Agnieszka Falenska, Marina Haid, Ngoc Thang Vu, Jonas Kuhn:
IMSurReal: IMS at the Surface Realization Shared Task 2019. 50-58 - Thiago Castro Ferreira, Emiel Krahmer:
Surface Realization Shared Task 2019 (MSR19): The Team 6 Approach. 59-62 - Farhood Farahnak, Laya Rafiee, Leila Kosseim, Thomas Fevens:
The Concordia NLG Surface Realizer at SRST 2019. 63-67 - Kartikeya Upasani, David King, Jinfeng Rao, Anusha Balakrishnan, Michael White:
The OSU/Facebook Realizer for SRST 2019: Seq2Seq Inflection and Serialized Tree2Tree Linearization. 68-74 - Xudong Hong, Ernie Chang, Vera Demberg:
Improving Language Generation from Feature-Rich Tree-Structured Data with Relational Graph Convolutional Encoders. 75-80 - Alessandro Mazzei, Valerio Basile:
The DipInfoUniTo Realizer at SRST'19: Learning to Rank and Deep Morphology Prediction for Multilingual Surface Realization. 81-87 - Anastasia Shimorina, Claire Gardent:
LORIA / Lorraine University at Multilingual Surface Realisation 2019. 88-93 - Marco Antonio Sobrevilla Cabezudo, Simon Mille, Thiago A. S. Pardo:
Back-Translation as Strategy to Tackle the Lack of Corpus in Natural Language Generation from Semantic Representations. 94-103
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