Introduction
Tencent’s Hunyuan staff has launched Hunyuan-MT-7B (a translation mannequin) and Hunyuan-MT-Chimera-7B (an ensemble mannequin). Each fashions are designed particularly for multilingual machine translation and have been launched along with Tencent’s participation within the WMT2025 Basic Machine Translation shared job, the place Hunyuan-MT-7B ranked first in 30 out of 31 language pairs.
Mannequin Overview
Hunyuan-MT-7B
- A 7B parameter translation mannequin.
- Helps mutual translation throughout 33 languages, together with Chinese language ethnic minority languages corresponding to Tibetan, Mongolian, Uyghur, and Kazakh.
- Optimized for each high-resource and low-resource translation duties, attaining state-of-the-art outcomes amongst fashions of comparable dimension.
Hunyuan-MT-Chimera-7B
- An built-in weak-to-strong fusion mannequin.
- Combines a number of translation outputs at inference time and produces a refined translation utilizing reinforcement studying and aggregation strategies.
- Represents the first open-source translation mannequin of this sort, enhancing translation high quality past single-system outputs.
Coaching Framework
The fashions have been skilled utilizing a five-stage framework designed for translation duties:
- Basic Pre-training
- 1.3 trillion tokens overlaying 112 languages and dialects.
- Multilingual corpora assessed for data worth, authenticity, and writing model.
- Variety maintained by means of disciplinary, trade, and thematic tagging techniques.
- MT-Oriented Pre-training
- Monolingual corpora from mC4 and OSCAR, filtered utilizing fastText (language ID), minLSH (deduplication), and KenLM (perplexity filtering).
- Parallel corpora from OPUS and ParaCrawl, filtered with CometKiwi.
- Replay of basic pre-training knowledge (20%) to keep away from catastrophic forgetting.
- Supervised Fantastic-Tuning (SFT)
- Stage I: ~3M parallel pairs (Flores-200, WMT check units, curated Mandarin–minority knowledge, artificial pairs, instruction-tuning knowledge).
- Stage II: ~268k high-quality pairs chosen by means of automated scoring (CometKiwi, GEMBA) and guide verification.
- Reinforcement Studying (RL)
- Algorithm: GRPO.
- Reward capabilities:
- XCOMET-XXL and DeepSeek-V3-0324 scoring for high quality.
- Terminology-aware rewards (TAT-R1).
- Repetition penalties to keep away from degenerate outputs.
- Weak-to-Robust RL
- A number of candidate outputs generated and aggregated by means of reward-based output
- Utilized in Hunyuan-MT-Chimera-7B, enhancing translation robustness and lowering repetitive errors.
Benchmark Outcomes
Computerized Analysis
- WMT24pp (English⇔XX): Hunyuan-MT-7B achieved 0.8585 (XCOMET-XXL), surpassing bigger fashions like Gemini-2.5-Professional (0.8250) and Claude-Sonnet-4 (0.8120).
- FLORES-200 (33 languages, 1056 pairs): Hunyuan-MT-7B scored 0.8758 (XCOMET-XXL), outperforming open-source baselines together with Qwen3-32B (0.7933).
- Mandarin⇔Minority Languages: Scored 0.6082 (XCOMET-XXL), larger than Gemini-2.5-Professional (0.5811), exhibiting important enhancements in low-resource settings.
Comparative Outcomes
- Outperforms Google Translator by 15–65% throughout analysis classes.
- Outperforms specialised translation fashions corresponding to Tower-Plus-9B and Seed-X-PPO-7B regardless of having fewer parameters.
- Chimera-7B provides ~2.3% enchancment on FLORES-200, notably in Chinese language⇔Different and non-English⇔non-Chinese language translations.
Human Analysis
A customized analysis set (overlaying social, medical, authorized, and web domains) in contrast Hunyuan-MT-7B with state-of-the-art fashions:
- Hunyuan-MT-7B: Avg. 3.189
- Gemini-2.5-Professional: Avg. 3.223
- DeepSeek-V3: Avg. 3.219
- Google Translate: Avg. 2.344
This exhibits that Hunyuan-MT-7B, regardless of being smaller at 7B parameters, approaches the standard of a lot bigger proprietary fashions.
Case Research
The report highlights a number of real-world circumstances:
- Cultural References: Accurately interprets “小红薯” because the platform “REDnote,” not like Google Translate’s “candy potatoes.”
- Idioms: Interprets “You might be killing me” as “你真要把我笑死了” (expressing amusement), avoiding literal misinterpretation.
- Medical Phrases: Interprets “uric acid kidney stones” exactly, whereas baselines generate malformed outputs.
- Minority Languages: For Kazakh and Tibetan, Hunyuan-MT-7B produces coherent translations, the place baselines fail or output nonsensical textual content.
- Chimera Enhancements: Provides enhancements in gaming jargon, intensifiers, and sports activities terminology.
Conclusion
Tencent’s launch of Hunyuan-MT-7B and Hunyuan-MT-Chimera-7B establishes a brand new commonplace for open-source translation. By combining a rigorously designed coaching framework with specialised deal with low-resource and minority language translation, the fashions obtain high quality on par with or exceeding bigger closed-source techniques. The launch of those 2 fashions offers the AI analysis neighborhood with accessible, high-performance instruments for multilingual translation analysis and deployment.
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