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20242026
most citedQwen3-TTS Technical Report

1 citations · 1 across the 3 of their papers we have counts for

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cs.CL2026

SASFT: Sparse Autoencoder-guided Supervised Finetuning to Mitigate Unexpected Code-Switching in LLMs

Boyi Deng, Yu Wan, Baosong Yang +3

Large Language Models (LLMs) have impressive multilingual capabilities, but they suffer from unexpected code-switching, also known as language mixing, which involves switching to u…

cs.CL2025

A Systematic Assessment of Language Models with Linguistic Minimal Pairs in Chinese

Yikang Liu, Yeting Shen, Hongao Zhu +9

We present ZhoBLiMP, the largest linguistic minimal pair benchmark for Chinese, with over 100 paradigms, ranging from topicalization to the \textit{Ba} construction. We then train…

cs.CL2025

PolyMath: Evaluating Mathematical Reasoning in Multilingual Contexts

Yiming Wang, Pei Zhang, Jialong Tang +12

In this paper, we introduce PolyMath, a multilingual mathematical reasoning benchmark covering 18 languages and 4 easy-to-hard difficulty levels. Our benchmark ensures difficulty c…

cs.CL2025

Sampling-Efficient Test-Time Scaling: Self-Estimating the Best-of-N Sampling in Early Decoding

Yiming Wang, Pei Zhang, Siyuan Huang +4

Test-time scaling enhances large language model performance by allocating additional compute resources during inference. Best-of-N (BoN) sampling serves as a common sampling-based…

cs.CL2025

PART: Progressive Alignment Representation Training for Multilingual Speech-To-Text with LLMs

Pei Zhang, Andong Chen, Xi Chen +3

Large language models (LLMs) have expanded from text to speech, giving rise to Speech Large Models (SLMs) that support recognition, translation, and synthesis. A key challenge is a…

cs.CL2025

Qwen3-Omni Technical Report

Jin Xu, Zhifang Guo, Hangrui Hu +35

We present Qwen3-Omni, a single multimodal model that, for the first time, maintains state-of-the-art performance across text, image, audio, and video without any degradation relat…