Here Are the Top 10 Most Influential Research Papers on Neural Machine Translation
The most-cited neural machine translation research papers show how NMT came to dominate the field — and how academia and industry’s interests have evolved.
The most-cited neural machine translation research papers show how NMT came to dominate the field — and how academia and industry’s interests have evolved.
Four college students harnessed recent Google Cloud releases to build a translation app that works offline and makes forms accessible to users with disabilities.
Neural machine translation experts weigh in on Google’s open sourcing of Lingvo, a sequence modeling framework built on TensorFlow.
Harvard and Systran publish a paper on their open-source neural machine translation model, OpenNMT. Research toolkit is a complete NMT implementation. Creators hope it will become the Moses of NMT.
“Google, we promise we are not taking you on,” says the Harvard NLP group as a research project draws Systran’s attention and is co-developed into open-source NMT. Systran expects competitors to quickly build products based on the technology.
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