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most citedExploration and Exploitation: Two Ways to Improve Chinese Spelling Correction Models

2 citations · 2 across the 5 of their papers we have counts for

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cs.CL2025

Parallel Scaling Law: Unveiling Reasoning Generalization through A Cross-Linguistic Perspective

Wen Yang, Junhong Wu, Chong Li +2

Recent advancements in Reinforcement Post-Training (RPT) have significantly enhanced the capabilities of Large Reasoning Models (LRMs), sparking increased interest in the generaliz…

cs.CL2025

Discovering Semantic Subdimensions through Disentangled Conceptual Representations

Yunhao Zhang, Shaonan Wang, Nan Lin +3

Understanding the core dimensions of conceptual semantics is fundamental to uncovering how meaning is organized in language and the brain. Existing approaches often rely on predefi…

cs.CL2025

Group then Scale: Dynamic Mixture-of-Experts Multilingual Language Model

Chong Li, Yingzhuo Deng, Jiajun Zhang +1

The curse of multilinguality phenomenon is a fundamental problem of multilingual Large Language Models (LLMs), where the competition between massive languages results in inferior p…

cs.CL2025

TokAlign: Efficient Vocabulary Adaptation via Token Alignment

Chong Li, Jiajun Zhang, Chengqing Zong

Tokenization serves as a foundational step for Large Language Models (LLMs) to process text. In new domains or languages, the inefficiency of the tokenizer will slow down the train…

cs.CL20212 cited

Exploration and Exploitation: Two Ways to Improve Chinese Spelling Correction Models

Chong Li, Cenyuan Zhang, Xiaoqing Zheng +1

A sequence-to-sequence learning with neural networks has empirically proven to be an effective framework for Chinese Spelling Correction (CSC), which takes a sentence with some spe…