Pith. sign in

REVIEW

XNMT: The eXtensible Neural Machine Translation Toolkit

Not yet reviewed by Pith; the record is open.

Re-run · record.json Download PDF Read on arXiv ↗

This paper has not been read by Pith yet. Machine review is queued; the pith claim, tier, and objections will appear here once it completes.

SPECIMEN: schema-true, not a live event

T0 review · schema-true

One-sentence machine reading of the paper's core claim.

pith:XXXXXXXX · record.json · timestamp

arxiv 1803.00188 v1 pith:YK3PQCE7 submitted 2018-03-01 cs.CL

XNMT: The eXtensible Neural Machine Translation Toolkit

Graham Neubig , Matthias Sperber , Xinyi Wang , Matthieu Felix , Austin Matthews , Sarguna Padmanabhan , Ye Qi , Devendra Singh Sachan
show 5 more authors
Philip Arthur Pierre Godard John Hewitt Rachid Riad Liming Wang
This is my paper
classification cs.CL
keywords xnmtmachinetranslationdesignextensibleneuralopen-sourcetoolkit
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
0 comments
read the original abstract

This paper describes XNMT, the eXtensible Neural Machine Translation toolkit. XNMT distin- guishes itself from other open-source NMT toolkits by its focus on modular code design, with the purpose of enabling fast iteration in research and replicable, reliable results. In this paper we describe the design of XNMT and its experiment configuration system, and demonstrate its utility on the tasks of machine translation, speech recognition, and multi-tasked machine translation/parsing. XNMT is available open-source at https://github.com/neulab/xnmt

discussion (0)

Sign in with ORCID, Apple, or X to comment. Anyone can read and Pith papers without signing in.