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        <title>Full-Video Context and Anonymous Candidate Selection for WMT26 Video Subtitle Translation</title>
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        <namePart type="given">Jianfeng</namePart>
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    <abstract>We present ReopenAI’s constrained-track system for the WMT26 Video Subtitle Translation Shared Task. The system translates Simplified Chinese subtitles into English, Thai, Indonesian, Malay, and Traditional Chinese for Taiwan. It combines Hy-MT2-7B and Gemma-4-12B-it without fine-tuning, using approximately 19B unique parameters. Both models receive the complete Chinese subtitle sequence and video titles as context and generate two candidates for each subtitle cue. A Gemma-based selector anonymously compares four candidates in a stable order and its reverse. A selection is accepted only when both judgments agree; otherwise, a deterministic Gemma candidate is used as fallback. In the official preliminary evaluation, ReopenAI ranked first overall and in every target direction, achieving a macro-average score of 89.357 across 100 videos. On an internal three-video diagnostic covering 705 cues per target, the fusion system achieved a 93.8% pooled acceptable-translation rate. A separate 122-cue ablation showed that full-video context improved Hy-MT2 in all five target languages, with gains ranging from 4.1 to 18.0 points. The system uses no task-specific parallel data, audio, or video frames.</abstract>
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%0 Conference Proceedings
%T Full-Video Context and Anonymous Candidate Selection for WMT26 Video Subtitle Translation
%A Wu, Jianfeng
%Y Haddow, Barry
%Y Kocmi, Tom
%Y Koehn, Philipp
%Y Monz, Christof
%S Proceedings of the Eleventh Conference on Machine Translation
%D 2026
%8 October
%I Association for Computational Linguistics
%C Budapest, Hungary
%@ 979-8-89176-474-3
%F wu-2026-full
%X We present ReopenAI’s constrained-track system for the WMT26 Video Subtitle Translation Shared Task. The system translates Simplified Chinese subtitles into English, Thai, Indonesian, Malay, and Traditional Chinese for Taiwan. It combines Hy-MT2-7B and Gemma-4-12B-it without fine-tuning, using approximately 19B unique parameters. Both models receive the complete Chinese subtitle sequence and video titles as context and generate two candidates for each subtitle cue. A Gemma-based selector anonymously compares four candidates in a stable order and its reverse. A selection is accepted only when both judgments agree; otherwise, a deterministic Gemma candidate is used as fallback. In the official preliminary evaluation, ReopenAI ranked first overall and in every target direction, achieving a macro-average score of 89.357 across 100 videos. On an internal three-video diagnostic covering 705 cues per target, the fusion system achieved a 93.8% pooled acceptable-translation rate. A separate 122-cue ablation showed that full-video context improved Hy-MT2 in all five target languages, with gains ranging from 4.1 to 18.0 points. The system uses no task-specific parallel data, audio, or video frames.
%U https://aclanthology.org/2026.wmt-main.207/
%P 2631-2636

Markdown (Informal)

[Full-Video Context and Anonymous Candidate Selection for WMT26 Video Subtitle Translation](https://aclanthology.org/2026.wmt-main.207/) (Wu, WMT 2026)

• Full-Video Context and Anonymous Candidate Selection for WMT26 Video Subtitle Translation (Wu, WMT 2026)

ACL

• Jianfeng Wu. 2026. Full-Video Context and Anonymous Candidate Selection for WMT26 Video Subtitle Translation. In Proceedings of the Eleventh Conference on Machine Translation, pages 2631–2636, Budapest, Hungary. Association for Computational Linguistics.