Papers with offline translation
The FISKMÖ Project: Resources and Tools for Finnish-Swedish Machine Translation and Cross-Linguistic Research (2020.lrec-1)
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Jörg Tiedemann, Tommi Nieminen, Mikko Aulamo, Jenna Kanerva, Akseli Leino, Filip Ginter, Niko Papula
| Challenge: | Finnish and Swedish are the two official languages of Finland. |
| Approach: | They propose to compile a massive corpus of translated material between Finnish and Swedish . they also aim to develop open and freely accessible translation services for those two languages . |
| Outcome: | The project aims to develop open and freely accessible translation services for Finnish and Swedish. |
SeqPO-SiMT: Sequential Policy Optimization for Simultaneous Machine Translation (2025.findings-acl)
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| Challenge: | SeqPO-SiMT is a new policy optimization framework for simultaneous machine translation that combines a tailored reward with a single step task. |
| Approach: | They propose a new policy optimization framework that defines the simultaneous machine translation task as a sequential decision making problem with a tailored reward. |
| Outcome: | The proposed framework outperforms the supervised fine-tuning model by 1.13 points while reducing the Average Lagging by 6.17 in the NEWSTEST2021 En Zh dataset. |
LLMs Can Achieve High-quality Simultaneous Machine Translation as Efficiently as Offline (2025.findings-acl)
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| Challenge: | Large language models perform well in offline machine translation when the complete source sentence is provided . however, in many real scenarios, the source tokens arrive in a streaming manner and simultaneous machine translation is required . |
| Approach: | They propose a new paradigm that includes constructing supervised fine-tuning data for simultaneous machine translation (SiMT) to achieve SiMT, source and target tokens are rearranged into interleaved sequences, separated by special tokens according to varying latency requirements. |
| Outcome: | The proposed approach achieves state-of-the-art performance across various SiMT benchmarks and evaluation metrics while maintaining efficient auto-regressive decoding. |
Simul-COMET: A Quality Metric for Simultaneous Interpretation in Distant Language Pair Considering Word Order Difference (2026.findings-acl)
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| Challenge: | Simultaneous interpretation (SI) uses segmenting of source speech into chunks and translating them in order. |
| Approach: | They propose a variation of COMET that measures monotonicity for simultaneous interpretation . they train Simul-COMET on offline translation data and show stronger alignment with evaluation scores . |
| Outcome: | The proposed model shows stronger alignment with evaluation scores provided by interpreters than COMET. |