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        <title>Multi-agentMT: Deploying AI Agent in the WMT25 Shared Task</title>
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            <title>Proceedings of the Tenth Conference on Machine Translation</title>
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    <abstract>We present Multi-agentMT, our system for the WMT25 General Shared Task. The model adopts Prompt Chaining, a multi-agent workflow combined with Rubric-MQM, an automatic MQM-based error annotation metric. Our primary submission follows a Translate–Postedit–Proofread pipeline, in which error positions are explicitly marked and iteratively refined. Results suggest that a semi-autonomous agent scheme for machine translation is feasible with a smaller, earlier-generation model in low-resource settings, achieving comparable quality at roughly half the cost of larger systems.</abstract>
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%0 Conference Proceedings
%T Multi-agentMT: Deploying AI Agent in the WMT25 Shared Task
%A Kim, Ahrii
%Y Haddow, Barry
%Y Kocmi, Tom
%Y Koehn, Philipp
%Y Monz, Christof
%S Proceedings of the Tenth Conference on Machine Translation
%D 2025
%8 November
%I Association for Computational Linguistics
%C Suzhou, China
%@ 979-8-89176-341-8
%F kim-2025-multi
%X We present Multi-agentMT, our system for the WMT25 General Shared Task. The model adopts Prompt Chaining, a multi-agent workflow combined with Rubric-MQM, an automatic MQM-based error annotation metric. Our primary submission follows a Translate–Postedit–Proofread pipeline, in which error positions are explicitly marked and iteratively refined. Results suggest that a semi-autonomous agent scheme for machine translation is feasible with a smaller, earlier-generation model in low-resource settings, achieving comparable quality at roughly half the cost of larger systems.
%U https://aclanthology.org/2025.wmt-1.53/
%P 769-777

Markdown (Informal)

[Multi-agentMT: Deploying AI Agent in the WMT25 Shared Task](https://aclanthology.org/2025.wmt-1.53/) (Kim, WMT 2025)

• Multi-agentMT: Deploying AI Agent in the WMT25 Shared Task (Kim, WMT 2025)

ACL

• Ahrii Kim. 2025. Multi-agentMT: Deploying AI Agent in the WMT25 Shared Task. In Proceedings of the Tenth Conference on Machine Translation, pages 769–777, Suzhou, China. Association for Computational Linguistics.