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models (LLMs) have become significantly more difficult to detect, as a poisoned parameter update is harder to recognise than a poisoned dataset. Therefore, several methods have been developed recently to
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Related works: [1] Sagawa et al., Distributionally Robust Neural Networks for Group Shifts (GroupDRO) https://arxiv.org/pdf/1911.08731 [2] Liu et al., Just Train Twice: Improving Group Robustness Without
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The Fraunhofer Institute for Secure Information Technology SIT is one of the leading research and development institutions for cybersecurity in Germany and Europe and is part of ATHENE, the national
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our own data and models. Based on the developed methods, it should then be evaluated whether (1) reliable detection of erotic clothing is possible and (2) whether erotic and pornographic images can be
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are suitable for addressing the question. Gaps in existing datasets and models should be described and filled with our own data and models. Based on the developed methods, it should then be evaluated whether (1
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optimization of technical processes and products. We present the exciting range of applications of our collaborative software development MESHFREE: https://www.meshfree.eu/ Currently, our team is working
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Institute for Solar Energy Systems ISE, we develop high-efficiency solar cells and the concentrator photovoltaic (CPV) module technology built on them. The so-called III-V multi-junction solar cells consist
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cell has already achieved a record efficiency of 68.9%. (https://doi.org/10.1002/pssr.202100113) . The thin-film processing of such III-V devices is a crucial building block for maximum efficiency, as it
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digitization. More than 400 employees – including around 100 students – from over 50 countries work at nine locations in scientific and non-scientific teams on the development of innovative methods to accelerate
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digitization. More than 400 employees – including around 100 students – from over 50 countries work at nine locations in scientific and non-scientific teams on the development of innovative methods to accelerate