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of LLM agents. These attacks exploit the agent’s ability to store, retrieve, and adapt knowledge over time, leading to biased decisions, manipulation of real-time behavior, security breaches, and system
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of real-time behavior, security breaches, and system-wide failures. The goal of this project is to develop a theoretical foundation for understanding and mitigating memory poisoning in LLM agents
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equations. Your main research assignments will be to develop new models and methods for generative sampling and Bayesian inference. You will be jointly supervised by Assistant Prof. Zheng Zhao (https
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formally based at the Division of Statistics and Machine Learning (STIMA) within the Department of Computer and Information Science . At STIMA, we conduct research and education in both statistics and
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Innovative city . The position is formally based at the Division of Statistics and Machine Learning (STIMA) within the Department of Computer and Information Science . At STIMA, we conduct research and
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for the division is the Visualization Center C, a unique science center in Norrköping that engages the public through data-driven installations and 3D fulldome experiences. Read more at http
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) within the Department of Computer and Information Science . At STIMA we conduct research and education in both statistics and machine learning, at the undergraduate, advanced and PhD levels. We regularly
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the agent’s ability to store, retrieve, and adapt knowledge over time, leading to biased decisions, manipulation of real-time behavior, security breaches, and system-wide failures. The goal of this project is
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, design, and conduct cutting-edge research on power-efficient integrated circuits (ICs) and transceivers tailored for next-generation 6G systems. To ensure seamless integration, these front-end solutions
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, design, and conduct research on integrated circuits taking on the challenges of next generation communication systems. The project aims to investigate the feasibility and advantages of new design