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20152026
most citedPrompting Large Language Model for Machine Translation: A Case Study

68 citations · 234 across the 28 of their papers we have counts for

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Showing 2023 · cs.CLShow all

5 papers · 2 filters

cs.CL2023

Towards Effective Disambiguation for Machine Translation with Large Language Models

Vivek Iyer, Pinzhen Chen, Alexandra Birch

Resolving semantic ambiguity has long been recognised as a central challenge in the field of Machine Translation. Recent work on benchmarking translation performance on ambiguous s…

cs.CL2023★ 4 cited

An Open Dataset and Model for Language Identification

Laurie Burchell, Alexandra Birch, Nikolay Bogoychev +1

Language identification (LID) is a fundamental step in many natural language processing pipelines. However, current LID systems are far from perfect, particularly on lower-resource…

cs.CL2023

When Does Monolingual Data Help Multilingual Translation: The Role of Domain and Model Scale

Christos Baziotis, Biao Zhang, Alexandra Birch +1

Multilingual machine translation (MMT), trained on a mixture of parallel and monolingual data, is key for improving translation in low-resource language pairs. However, the literat…

cs.CL2023★ 13 cited

Hallucinations in Large Multilingual Translation Models

Nuno M. Guerreiro, Duarte Alves, Jonas Waldendorf +4

Large-scale multilingual machine translation systems have demonstrated remarkable ability to translate directly between numerous languages, making them increasingly appealing for r…

cs.CL2023★ 68 cited

Prompting Large Language Model for Machine Translation: A Case Study

Biao Zhang, Barry Haddow, Alexandra Birch

Research on prompting has shown excellent performance with little or even no supervised training across many tasks. However, prompting for machine translation is still under-explor…