Apr 8, 2022 · In this work, we address the specific issues of collaborative NMT, such as estimating the latency required to generate the (unknown) output sequence.
Dec 1, 2022 · PDF | On May 28, 2022, Yukai Chen and others published C-NMT: A Collaborative Inference Framework for Neural Machine Translation | Find, ...
Our experiments show that CI can reduce the latency of NMT by up to 44% compared to a non-collaborative approach. Index Terms—Machine Translation, Collaborative ...
The C-NMT Framework. 4. Experimental Results. 5. Conclusions. Outline. Page 11. • C-NMT: Collaborative Neural Machine Translation. • Encoder-Decoder ...
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C-NMT: A Collaborative Inference Framework for Neural Machine Translation ... OpenNMT: Open-Source Toolkit for Neural Machine Translation. Klein G., Kim Y ...
Collaborative Inference (CI) optimizes the latency and energy consumption of deep learning inference through the inter-operation of edge and cloud devices.
Collaborative Inference (CI) optimizes the latency and energy consumption of deep learning inference through the inter-operation of edge and cloud devices.
Collaborative Inference (CI) optimizes the latency and energy consumption of deep learning inference through the inter-operation of edge and cloud devices.
A Fast Neural Machine Translation System developed in C++. Topics. machine-translation transformer neural-machine-translation fast-decoding. Resources. Readme ...
Roberta Chiaro's 5 research works with 47 citations, including: C-NMT: A Collaborative Inference Framework for Neural Machine Translation.