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20242026
most citedWhy Not Transform Chat Large Language Models to Non-English?

1 citations · 1 across the 8 of their papers we have counts for

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8 papers

cs.CL2026

Unlocking Fine-Grained Translation Quality Estimation in LRMs through Mutually Boosting Implicit and Explicit Reasoning

Renfei Dang, Xinye Wang, Zhejian Lai +5

Large Reasoning Models (LRMs) still struggle with fine-grained translation quality estimation (QE), even with long reasoning chains. We argue that LRMs already possess strong multi…

cs.CL2026

TAPO: Translation Augmented Policy Optimization for Multilingual Mathematical Reasoning

Xu Huang, Zhejian Lai, Zixian Huang +2

Large Language Models (LLMs) have demonstrated remarkable proficiency in English mathematical reasoning, yet a significant performance disparity persists in multilingual contexts,…

cs.CL2026

R3S: Refining and Recovering Reinforcement Signals for Multilingual Understanding and Reasoning

Junxiao Liu, Zhijun Wang, Yixiao Li +6

Large reasoning models often default to English reasoning when processing non-English questions, yet their performance drops substantially when reasoning in the question language.…

cs.CL2025

Understanding New-Knowledge-Induced Factual Hallucinations in LLMs: Analysis and Interpretation

Renfei Dang, Peng Hu, Zhejian Lai +3

Prior works have shown that fine-tuning on new knowledge can induce factual hallucinations in large language models (LLMs), leading to incorrect outputs when evaluated on previousl…

cs.AI2025

AdaR: A Framework for Equipping LLMs with Adaptive Reasoning

Zhejian Lai, Xiang Geng, Zhijun Wang +7

Mathematical reasoning is a primary indicator of large language models (LLMs) intelligence. However, existing LLMs exhibit failures in robustness and generalization. This paper att…

cs.CL2025

How Does Alignment Enhance LLMs' Multilingual Capabilities? A Language Neurons Perspective

Shimao Zhang, Zhejian Lai, Xiang Liu +5

Multilingual Alignment is an effective and representative paradigm to enhance LLMs' multilingual capabilities, which transfers the capabilities from the high-resource languages to…

cs.CL2025

Alleviating Distribution Shift in Synthetic Data for Machine Translation Quality Estimation

Xiang Geng, Zhejian Lai, Jiajun Chen +2

Quality Estimation (QE) models evaluate the quality of machine translations without reference translations, serving as the reward models for the translation task. Due to the data s…

cs.CL2024★ 1 cited

Why Not Transform Chat Large Language Models to Non-English?

Xiang Geng, Ming Zhu, Jiahuan Li +14

The scarcity of non-English data limits the development of non-English large language models (LLMs). Transforming English-centric LLMs to non-English has been identified as an effe…