Zobrazeno 1 - 6
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pro vyhledávání: '"Fellicious, Christofer"'
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
Digital forensics is the process of extracting, preserving, and documenting evidence in digital devices. A commonly used method in digital forensics is to extract data from the main memory of a digital device. However, the main challenge is identifyi
Externí odkaz:
http://arxiv.org/abs/2209.05243
Autor:
Fellicious, Christofer
Autonomous Vehicles(AV) are one of the brightest promises of the future which would help cut down fatalities and improve travel time while working in harmony. Autonomous vehicles will face with challenging situations and experiences not seen before.
Externí odkaz:
http://arxiv.org/abs/1808.05443
Publikováno v:
Datenbank-Spektrum; Mar2024, Vol. 24 Issue 1, p53-62, 10p
