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cs.CL2025★ 1 cited
Mini-Omni-Reasoner: Token-Level Thinking-in-Speaking in Large Speech Models
Zhifei Xie, Ziyang Ma, Zihang Liu +7
Reasoning is essential for effective communication and decision-making. While recent advances in LLMs and MLLMs have shown that incorporating explicit reasoning significantly impro…
cs.CL2025
Slow Tuning and Low-Entropy Masking for Safe Chain-of-Thought Distillation
Ziyang Ma, Qingyue Yuan, Linhai Zhang +1
Previous chain-of-thought (CoT) distillation methods primarily focused on enhancing the reasoning capabilities of Small Language Models (SLMs) by utilizing high-quality rationales…
cs.CL2025
Large Language Models Have Intrinsic Meta-Cognition, but Need a Good Lens
Ziyang Ma, Qingyue Yuan, Zhenglin Wang +1
Previous research has primarily focused on the cognitive error detection capabilities of Large Language Models (LLMs), often prompting them to analyze mistakes in reasoning chains.…