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        <title>ASEAN-8B: A Prompted Qwen3.5-9B System for Chinese–Southeast Asian Web Translation</title>
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    <abstract>We present a training-free system for the WMT26 Chinese–Southeast Asian Multilingual Machine Translation Task. The system uses the publicly available Qwen3.5-9B model with a direction-specific prompt, non-thinking decoding, and single-pass generation. We first compare 17 models on a balanced 210-example development probe covering 14 translation directions between Chinese and seven Southeast Asian languages. We then evaluate the selected system on a separate 1,400-example probe containing 100 examples per direction. Using sentence-level sacreBLEU with the FLORES-200 tokenizer and COMET-22, Qwen3.5-9B achieves 24.86 BLEU, 83.23 COMET, and an equally weighted combined score of 54.04. Analysis reveals substantial variation across directions and highlights the effect of noisy website text and imperfect references on lexical and semantic metrics. The resulting system is compact, reproducible, and suitable for efficiency-aware evaluation under the task’s 20-billion-parameter limit.</abstract>
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%0 Conference Proceedings
%T ASEAN-8B: A Prompted Qwen3.5-9B System for Chinese–Southeast Asian Web Translation
%A Haobin, Wen
%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 haobin-2026-asean
%X We present a training-free system for the WMT26 Chinese–Southeast Asian Multilingual Machine Translation Task. The system uses the publicly available Qwen3.5-9B model with a direction-specific prompt, non-thinking decoding, and single-pass generation. We first compare 17 models on a balanced 210-example development probe covering 14 translation directions between Chinese and seven Southeast Asian languages. We then evaluate the selected system on a separate 1,400-example probe containing 100 examples per direction. Using sentence-level sacreBLEU with the FLORES-200 tokenizer and COMET-22, Qwen3.5-9B achieves 24.86 BLEU, 83.23 COMET, and an equally weighted combined score of 54.04. Analysis reveals substantial variation across directions and highlights the effect of noisy website text and imperfect references on lexical and semantic metrics. The resulting system is compact, reproducible, and suitable for efficiency-aware evaluation under the task’s 20-billion-parameter limit.
%U https://aclanthology.org/2026.wmt-main.180/
%P 2368-2373

Markdown (Informal)

[ASEAN-8B: A Prompted Qwen3.5-9B System for Chinese–Southeast Asian Web Translation](https://aclanthology.org/2026.wmt-main.180/) (Haobin, WMT 2026)

• ASEAN-8B: A Prompted Qwen3.5-9B System for Chinese–Southeast Asian Web Translation (Haobin, WMT 2026)

ACL

• Wen Haobin. 2026. ASEAN-8B: A Prompted Qwen3.5-9B System for Chinese–Southeast Asian Web Translation. In Proceedings of the Eleventh Conference on Machine Translation, pages 2368–2373, Budapest, Hungary. Association for Computational Linguistics.