Word Representation Models for Morphologically Rich Languages in Neural
Machine Translation

Word Representation Models for Morphologically Rich Languages in Neural Machine Translation

14 June 2016

Ekaterina Vylomova

Gholamreza Haffari

Papers citing "Word Representation Models for Morphologically Rich Languages in Neural Machine Translation"

10 / 10 papers shown

Title
NxPlain: Web-based Tool for Discovery of Latent Concepts Fahim Dalvi Nadir Durrani Hassan Sajjad Tamim Jaban Musab Husaini Ummar Abbas 15 1 0 06 Mar 2023
Log-linear Guardedness and its Implications Shauli Ravfogel Yoav Goldberg Ryan Cotterell 28 2 0 18 Oct 2022
Discovering Latent Concepts Learned in BERT Fahim Dalvi A. Khan Firoj Alam Nadir Durrani Jia Xu Hassan Sajjad SSL 11 56 0 15 May 2022
How Suitable Are Subword Segmentation Strategies for Translating Non-Concatenative Morphology? Chantal Amrhein Rico Sennrich 27 13 0 02 Sep 2021
How transfer learning impacts linguistic knowledge in deep NLP models? Nadir Durrani Hassan Sajjad Fahim Dalvi 13 48 0 31 May 2021
Dynamic Programming Encoding for Subword Segmentation in Neural Machine Translation Xuanli He Gholamreza Haffari Mohammad Norouzi 19 45 0 03 May 2020
On the Linguistic Representational Power of Neural Machine Translation Models Yonatan Belinkov Nadir Durrani Fahim Dalvi Hassan Sajjad James R. Glass MILM 33 68 0 01 Nov 2019
CMU-01 at the SIGMORPHON 2019 Shared Task on Crosslinguality and Context in Morphology Aditi Chaudhary Elizabeth Salesky G. Bhat David R. Mortensen J. Carbonell Yulia Tsvetkov 24 4 0 23 Jul 2019
Improving Character-based Decoding Using Target-Side Morphological Information for Neural Machine Translation Peyman Passban Qun Liu Andy Way 9 28 0 17 Apr 2018
What do Neural Machine Translation Models Learn about Morphology? Yonatan Belinkov Nadir Durrani Fahim Dalvi Hassan Sajjad James R. Glass 52 410 0 11 Apr 2017