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pro vyhledávání: '"Wendlinger, Lorenz"'
Autor:
Wendlinger, Lorenz, Braun, Christian, Zubaer, Abdullah Al, Nonn, Simon Alexander, Großkopf, Sarah, Fellicious, Christofer, Granitzer, Michael
We show that current open-source foundational LLMs possess instruction capability and German legal background knowledge that is sufficient for some legal analysis in an educational context. However, model capability breaks down in very specific tasks
Externí odkaz:
http://arxiv.org/abs/2412.15902
Autor:
Fellicious, Christofer, Wendlinger, Lorenz, Gancarski, Mario, Mitrovic, Jelena, Granitzer, Michael
Supervised machine learning often encounters concept drift, where the data distribution changes over time, degrading model performance. Existing drift detection methods focus on identifying these shifts but often overlook the challenge of acquiring l
Externí odkaz:
http://arxiv.org/abs/2411.02995
Publikováno v:
In Proceedings of the 39th ACM/SIGAPP Symposium on Applied Computing, pp. 368-369. 2024
In real-world applications, input data distributions are rarely static over a period of time, a phenomenon known as concept drift. Such concept drifts degrade the model's prediction performance, and therefore we require methods to overcome these issu
Externí odkaz:
http://arxiv.org/abs/2407.06543
Akademický článek
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