arXiv:1903.07402
공식 코드 · Papers with Code
Neutron: An Implementation of the Transformer Translation Model and its Variants
원문 초록
The Transformer translation model is easier to parallelize and provides better performance compared to recurrent seq2seq models, which makes it popular among industry and research community. We implement the Neutron in this work, including the Transformer model and its several variants from most recent researches. It is highly optimized, easy to modify and provides comparable performance with interesting features while keeping readability.
함께 살펴볼 논문
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CycleVAR: Repurposing Autoregressive Model for Unsupervised One-Step Image Translation
CycleDistill: Bootstrapping Machine Translation using LLMs with Cyclical Distillation
Gender Bias in English-to-Greek Machine Translation
Mutual-Supervised Learning for Sequential-to-Parallel Code Translation
TACTIC: Translation Agents with Cognitive-Theoretic Interactive Collaboration
How Programming Concepts and Neurons Are Shared in Code Language Models
토론
이 논문과 연결된 포럼 글이 아직 없습니다.