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Found 7 papers, 6 papers with code
SiLLM: Large Language Models for Simultaneous Machine Translation
We propose SiLLM, which delegates the two sub-tasks to separate agents, thereby incorporating LLM into SiMT.
Non-autoregressive Streaming Transformer for Simultaneous Translation
Simultaneous machine translation (SiMT) models are trained to strike a balance between latency and translation quality.
Simultaneous Machine Translation with Tailored Reference
Training the model with ground-truth at low latency may introduce forced anticipations, whereas utilizing reference consistent with the source word order at high latency results in performance degradation.
Glancing Future for Simultaneous Machine Translation
Simultaneous machine translation (SiMT) outputs translation while reading the source sentence.
Learning Optimal Policy for Simultaneous Machine Translation via Binary Search
Simultaneous machine translation (SiMT) starts to output translation while reading the source sentence and needs a precise policy to decide when to output the generated translation.
Turning Fixed to Adaptive: Integrating Post-Evaluation into Simultaneous Machine Translation
Compared to the fixed policy, the adaptive policy achieves better latency-quality tradeoffs by adopting a flexible translation policy.
Wait-info Policy: Balancing Source and Target at Information Level for Simultaneous Machine Translation
In this paper, we propose a Wait-info Policy to balance source and target at the information level.
