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个人简介
My research is centred around the risks and promises of large ML models for human-centered AI. I expore how to leverage the capabilities of these models’ for the best while accounting for and mitigating the issues arising from large-scale training. Latest advances in deep learning have been highly data-driven, relying on billion-sized datasets randomly scraped from the internet. In my research I investigate what models actually learn during pre-training and how to measure and utilize the model's representations. With the goal of improving how we as humans interact with AI systems, making the AI align with the behavior us humans expect from the system.
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CVPR 2023 (2023): 22522-22531
Manuel Brack,Felix Friedrich, Katharina Kornmeier, Linoy Tsaban,Patrick Schramowski,Kristian Kersting, Apolinário Passos
CVPR 2024 (2023)
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