Biqing Qi is currently a research scientist at the Shanghai AI Lab. He received his Ph.D. from the Key Laboratory of Autonomous Intelligent Unmanned Systems (AIUS) at Harbin Institute of Technology, under the joint supervision of the Center for Collaborative & Conversational Intelligence (C3I) at Tsinghua University, guided by Professors Bowen Zhou and Ligang Wu. He serves as a committee member of the Embodied Intelligence Committee of the Chinese Information Processing Society, with his research focusing on machine learning theory, foundational models, and human-machine collaborative systems. His research has contributed to over 30 publications in top-tier conferences and journals, including NeurIPS, CVPR, ICLR, ACL, AAAI, EMNLP, NAACL, TNNLS, and TCSVT. His contributions include: 1) Co-developing the “General-Specialized Integration Intelligence” pathway for AGI with Professor Zhou Bowen’s team; 2) Introducing the concept and framework of interactive continual learning from the perspectives of System 1 and System 2; and 3) Pioneering the validation of a research paradigm for independent hypothesis generation driven by large language models (LLMs). His work has garnered significant media attention and has been implemented in leading technology companies such as Tencent, ByteDance, and Xianyuan. Additionally, he has played a pivotal role in more than ten major projects, including two under the Ministry of Science and Technology’s 2030 Key Special Project, two major R&D initiatives, and several key projects funded by the National Natural Science Foundation. He has led a Shanghai Municipal Science and Technology Commission project and has been selected for an overseas dispatch program.

齐弼卿,上海人工智能实验室青年科学家,哈工大、清华联培博士,博士生导师周伯文与吴立刚教授。中文信息学会具生智能专委会委员,研究领域包括可持续机器学习理论、基础模型及人机协同系统。在NeurIPS、CVPR、ICLR、ACL、AAAI、EMNLP、NAACL、TNNLS、TCSVT等国际高水平学术期刊和会议上发表论文30余篇。其主要贡献包括:1)与周伯文教授团队共同提出“通专融合智能”AGI发展路径;2)提出交互式持续学习概念与框架:系统和系统2视角;3)首次验证大模型驱动独立假设提出的研究范式,相关成果受到多家媒体关注与报道,并在腾讯、字节、衔远等科技公司落地应用。作为核心骨干,参与了十余项国家级重大科研项目,包括科技部2030重点专项、国家重大研发计划项目及国家自然科学基金重点项目等,作为课题负责人推动上海科委XX项目(亿级),并入选海外外派人才项目。

If you are seeking any form of academic collaborations with Shanghai AI Lab or AIUS, SCIR Lab at HIT and Tsinghua C3I Lab, please feel free to email me at qibiqing7@gmail.com or qibiqing@pjlab.org.cn

🔥 News

  • 2025.02: 🎉 One paper is accepted by CVPR 2025
  • 2025.02: 🔥”Can 1B LLM Surpass 405B LLM? Rethinking Compute-Optimal Test-Time Scaling” released on Project Page
  • 2025.01: 🎉 Two papers are accepted by ICLR 2025 and TCSVT 2025
  • 2024.12: 🎉 Two papers are accepted by AAAI 2025 (One Oral)
  • 2024.10: 🎉 Four papers are accepted by NeurIPS 2024(One Dataset Track)
  • 2024.09: 🎉 Two papers are accepted by EMNLP 2024 (One Findings)
  • 2024.07: 🎉 Two papers are accepted by COLM 2024 and ACM MM 2024
  • 2024.05: 🎉 Two papers are accepted by ACL 2024 (One Findings)
  • 2024.02: 🎉 Two papers are accepted by CVPR 2024 and SPL 2024
  • 2023.10: 🎉 Two papers are accepted by NAACL 2024 (Oral)
  • 2023.08: 🎉 Two papers are accepted by NeurIPS 2023 and TNNLS 2023

📝 Publications

  • Notes:(*)indicates the equal contributions and(^)indicates the corresponding author.

👁 Survey and Position Papers

上海人工智能实验室主任周伯文: 通专融合是实现AGI的战略路径之一
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🎙 Trustworthy Machine Learning theory

💣 Specialized Generalist Foundation Model and Technologies

世界人工智能大会报道: Interactive Continual Learning框架是实现通专融合的路径之一
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Interactive Continual Learning
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CVPR 2024 Interactive continual learning: Fast and slow thinking, Biqing Qi, Xinquan Chen, Junqi Gao, Dong Li, Jianxing Liu, Ligang Wu, Bowen Zhou,

  • This work was the first to propose the concept of interactive continual learning.
  • Instantiated through the Cognitive Complementarity Theory (System1 and System2).
  • An advanced continual learning framework with the novel structured key-value pairs memory unit.
  • A potential framework to develop Specialized Generalist AI.
Contrastive Augmented Graph2Graph Memory Interaction
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TCSVT 2025 Contrastive Augmented Graph2Graph Memory Interaction for Few Shot Continual Learning, Biqing Qi, Junqi Gao, Xingquan Chen, Dong Li, Jianxing Liu, Ligang Wu, Bowen Zhou

CoGenesis
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ACL 2024 CoGenesis: A Framework Collaborating Large and Small Language Models for Secure Context-Aware Instruction Following, Kaiyan Zhang, Jianyu Wang, Ermo Hua, Biqing Qi, Ning Ding, Bowen Zhou

PaD
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NAACL 2024 PaD: Program-aided Distillation Can Teach Small Models Reasoning Better than Chain-of-thought Fine-tuning, Xuekai Zhu, Biqing Qi, Kaiyan Zhang, Xinwei Long, Zhouhan Lin, Bowen Zhou

Online DPO
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Arxiv Online DPO: Online Direct Preference Optimization with Fast-Slow Chasing, Biqing Qi, Pengfei Li, Fangyuan Li, Junqi Gao, Kaiyan Zhang, Bowen Zhou

🌱 Specialized Generalist driven Multi-Agents Systems

👄 Specialized Generalist driven AI4S and Embodied Applications

🏂🏻 AI4S applications: Hypothesis Proposers

🤖 Embodied Applications

🌃 Teams

Shanghai AI Lab Interns

Foundation Models

  • Shuang Cheng, (2024.11-, 1st Ph.D., Zhejiang University), CIKM’24, etc.
  • Dawei Liu, (2024.11-, 1st Ph.D., Shanghai Jiao Tong University).
  • Yuhua Jiang, (2025.02-, 1st Ph.D., Tsinghua Univeristy), TWC’23,’24.
  • Xingfeng Yuan, (2024.12-, 2nd Master’s, Fudan University), EMNLP’23,’24.
  • Yiyao Yu, (2025.03-, 2nd Master’s, Tsinghua University), ACL‘24.

Multi-Agents Systems

  • Junqi Gao, (2024.9-, 2nd Ph.D., Harbin Institute of Technology), NIPS’23,’24, CVPR’24, ACL’24, etc.
  • Dong Li, (2024.10-, 2nd Ph.D., Harbin Institute of Technology), NIPS’24, CVPR’24, etc.
  • Runze Liu, (2024.10-, 2nd Master’s, Tsinghua University), ICLR’23, ICML’24, etc.
  • Xuetian Cheng, (2024.11-, 2nd Master’s, Fudan University), WWW’25 under review.
  • Yinghao Cheng, (2024.11-, 1st Ph.D., Tsinghua University).

AI4S and emboddied Applications

  • Zongling Li, (2024.12-, 2nd Master’s, Tsinghua University), TWC’24.
  • Linnan Chang, (2025.3-, 2nd Master’s, National University of Singapore), ICLR’24.
  • Siqi Song, (2025.2-, 1st Master’s, Tsinghua University).(Visiting Student)

Alumni Interns and Visiting Students

  • Gunbing Zhang, Yifan Hu, Yongjia Yu, Yu Zhang, Jing Xiao, Xunzhe Zhou.

⚔ Projects

Commodity Price Risk Prediction and Demonstration Application Sep.2023-Sep.2026

  • (Key Participants) National Science and Technology Major Project:
  • Responsible for the technical planning of Project 2 and leading the team in advancing the construction of the labeling system within LLMs.

Research on Theory and Applications of Human-AI Collaboration with LLMs Jan.2024-Jan.2027

  • (Key Participants) National Science and Technology Major Project:
  • Responsible for designing the project architecture, planning technical aspects, and overseeing the development of human-machine collaborative systems, along with conducting applied research in knowledge discovery for Project 3.

Cognitive Load Optimization in Human-Machine Collaboration Mar.2023-Dec.2026

  • (Participated) Key Research Program of the Ministry of Science and Technology in 2030:
  • Responsible for project management within Tsinghua Group, as well as interaction modeling and reflective framework optimization in LLMs.

Research for Product Insight, Design, Development to Marketing Innovation Sep.2023-Dec.2025

  • Participated)Beijing Municipal Science and Technology Commission Key Project.
  • Responsible for project architecture, planing technical aspects.

Proteomics Data based Knowledge Discovery Mar.2022-Dec.2023

  • (Student Lead) Preliminary Research Project for Major Scientific Plan.
  • Responsible for project architecture, planning technical aspects, and guiding the design of human-AI systems with respect to hypothesis proposers.

Demonstration of Personified Human-Machine Dialogue System Mar.2020-Dec.2023

  • (Participated) Key Research Program of the Ministry of Science and Technology in 2030:
  • Responsible for the development of a robust dialogue intent detection method.