I will soon be a research scientist at the Shanghai AI Lab. Prior to that, I received the Ph.D. with the Key Laboratory of Autonomous Intelligent Unmanned Systems (AIUS) in Control Science and Engineering at Harbin Institute of Technology, jointly supervised by the Center for Collaborative & Conversational Intelligence (C3I) at Tsinghua University under the supervision of Bowen Zhou and Ligang Wu.
Additionally, I collaborate closely with Jianxing Liu, Guanghui Sun at AIUS, and Weinan Zhang at the DT Group in SCIR Lab. Since February 2022, I have been interning at Frontis.AI in China.
My research interests include: 1) trustworthy and continual learning theory, 2) knowledge-compositional foundation models and 3) Multimodal human-AI collaboration systems.
My homepage is available at https://biqing-qi.github.io/.
If you are seeking any form of academic collaborations with AIUS, SCIR Lab at HIT, Tsinghua C3I Lab, or the Shanghai AI Lab, please feel free to email me at [[email protected]] or [[email protected]].
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【来个实习生广告】上海人工智能实验室招聘多智能体协同驱动知识发现方向实习生,欢迎各位老师同学多多推荐[跳跳]
【岗位名称】
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上海人工智能实验室
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AI算法研究实习生
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联系人:齐弼卿 星启青年研究员
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邮箱:[[email protected]]
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微信:18846835017
【岗位介绍】
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群体智能的理论分析: 研究多智能体协同学习与推理能力上限,为不同场景下模型组合提供指导,回答"合多少,怎么合"的问题。
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模型高效压缩重组技术: 通过对结构化知识存储的研究,我们旨在开发更灵活和可解释的模型知识存储解决方案,让我们能够根据需求灵活地高效"搭建"模型。
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高效多模型协同推理机制: 通过设计高效可靠的多模型联合推理方案,使模型能够在推理过程中实现自我纠错和反思,从而得出更可靠、准确的推理和决策。
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大模型驱动的群体智能系统设计: 研究通用和专业领域的合作策略,旨在构建一个层级化的模型"社交网络"。这将帮助通用大模型准确利用当前任务所需的能力和知识,实现通用和专业知识的融合,扩展模型的整体知识覆盖。
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研究框架可参考我们关于通专融合理念的position paper https://arxiv.org/pdf/2407.08642
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面向文章发表:AI顶会及Nature 子刊等顶级期刊
【岗位要求】
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良好的文献阅读能力与算法复现能力。
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熟悉Python编程语言,Pytorch框架或其他深度学习框架。
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至少能连续参加6个月的实习工作。
加分项:
- 在顶级会议或期刊上发表过自然语言处理、计算机视觉、多模态等相关领域论文;
- 具有开源项目经验或AI相关竞赛的成绩。
我们将提供:
- 充沛的AI计算资源、AI行业内知名专家的指导
- 对于优秀实习生,将提供转正或推荐读博机会(包括周伯文教授清华课题组等)
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