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In2x at WMT25 Translation Task

Published: August 20, 2025 | arXiv ID: 2508.14472v1

By: Lei Pang , Hanyi Mao , Quanjia Xiao and more

Potential Business Impact:

Helps computers translate rare languages well.

Business Areas:
Translation Service Professional Services

This paper presents the open-system submission by the In2x research team for the WMT25 General Machine Translation Shared Task. Our submission focuses on Japanese-related translation tasks, aiming to explore a generalizable paradigm for extending large language models (LLMs) to other languages. This paradigm encompasses aspects such as data construction methods and reward model design. The ultimate goal is to enable large language model systems to achieve exceptional performance in low-resource or less commonly spoken languages.

Country of Origin
πŸ‡ΊπŸ‡Έ πŸ‡¨πŸ‡³ China, United States

Page Count
8 pages

Category
Computer Science:
Computation and Language