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Found 3 papers, 2 papers with code
Addressing the Length Bias Problem in Document-Level Neural Machine Translation
To solve the length bias problem, we propose to improve the DNMT model in training method, attention mechanism, and decoding strategy.
Enhancing Neural Machine Translation with Semantic Units
Conventional neural machine translation (NMT) models typically use subwords and words as the basic units for model input and comprehension.
BayLing: Bridging Cross-lingual Alignment and Instruction Following through Interactive Translation for Large Language Models
To minimize human workload, we propose to transfer the capabilities of language generation and instruction following from English to other languages through an interactive translation task.
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