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From the 1 of 30 linked papers with an AI index.

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20242026
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cs.CL2026

A Data-Efficient Path to Multilingual LLMs: Language Expansion via Post-training PARAM Integration into Upcycled MoE

Hao Zhou, Tianhao Li, Zhijun Wang +6

Expanding Large Language Models~(LLMs) to new languages is a costly endeavor, demanding extensive Continued Pre-Training~(CPT) and data-intensive alignment. While recent data-free…

cs.CL2026

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.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

ExpLang: Improved Exploration and Exploitation in LLM Reasoning with On-Policy Thinking Language Selection

Changjiang Gao, Zixian Huang, Kaichen Yang +3

Current large reasoning models (LRMs) have shown strong ability on challenging tasks after reinforcement learning (RL) based post-training. However, previous work mainly focuses on…

cs.CL2025

Understanding LLMs' Cross-Lingual Context Retrieval: How Good It Is And Where It Comes From

Changjiang Gao, Hankun Lin, Xin Huang +5

Cross-lingual context retrieval (extracting contextual information in one language based on requests in another) is a fundamental aspect of cross-lingual alignment, but the perform…

cs.CL2025

EnAnchored-X2X: English-Anchored Optimization for Many-to-Many Translation

Sen Yang, Yu Bao, Yu Lu +3

Large language models (LLMs) have demonstrated strong machine translation capabilities for English-centric language pairs but underperform in direct non-English (x2x) translation.…