Hi👋 I am Zhouqi Hua (华洲琦).
I am a first year PhD student at Fudan University, in the joint program in Large Model Center of Shanghai AI Laboratory, advised by Dr. Wenwei Zhang, Dr. Kai Chen and Prof. Dahua Lin. Before that, I received the bachelor degree at Tongji University in 2025.
My research focus on generalization in LLMs, including length generalization and compositional generalization. Now I'm interested in investigating the mathematical abilities of LLMs.
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Shanghai AI LabResearch Intern @ Large Model Center
Joint Ph.D. StudentSep. 2025 - present -
Fudan UniversityPh.D. Student in Computer ScienceSep. 2025 - present
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Tongji UniversityB.S. in Computer ScienceSep. 2021 - Jul. 2025
Honors & Awards
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Tongji Excellent Student Award2024
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Tongji Excellent Student Scholarship (First Prize)2024
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National Second Prize in CCCC-MAIC2024
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Tongji Excellent Student Scholarship (First Prize)2023
News
Selected Publications (view all )
Intern-S1: A Scientific Multimodal Foundation Model
Lei Bai, Zhongrui Cai, ..., Zhouqi Hua, ..., Yu Qiao et al.
Preprint
Intern-S1 is a large multimodal MoE foundation model trained with massive scientific data and mixture-of-rewards reinforcement learning, achieving SOTA performance in scientific reasoning and professional tasks while remaining competitive in general reasoning among open-source models.
Intern-S1: A Scientific Multimodal Foundation Model
Lei Bai, Zhongrui Cai, ..., Zhouqi Hua, ..., Yu Qiao et al.
Preprint
Intern-S1 is a large multimodal MoE foundation model trained with massive scientific data and mixture-of-rewards reinforcement learning, achieving SOTA performance in scientific reasoning and professional tasks while remaining competitive in general reasoning among open-source models.
The Imitation Game: Turing Machine Imitator is Length Generalizable Reasoner
Zhouqi Hua*, Wenwei Zhang*#, Chengqi Lyu, Yuzhe Gu, Songyang Gao, Kuikun Liu, Dahua Lin#, Kai Chen# (* equal contribution, # corresponding author)
Under review.
Turing Machine Imitation Learning (TAIL) is a synthetic CoT framework that enhances the length generalization of LLMs on computable reasoning tasks by imitating Turing Machine execution, achieving state-of-the-art performance across 18 challenging tasks.
The Imitation Game: Turing Machine Imitator is Length Generalizable Reasoner
Zhouqi Hua*, Wenwei Zhang*#, Chengqi Lyu, Yuzhe Gu, Songyang Gao, Kuikun Liu, Dahua Lin#, Kai Chen# (* equal contribution, # corresponding author)
Under review.
Turing Machine Imitation Learning (TAIL) is a synthetic CoT framework that enhances the length generalization of LLMs on computable reasoning tasks by imitating Turing Machine execution, achieving state-of-the-art performance across 18 challenging tasks.