2 citations · 6 across the 7 of their papers we have counts for
8 papers
CoRECT: A Framework for Evaluating Embedding Compression Techniques at Scale
L. Caspari, M. Dinzinger, K. Ghosh Dastidar +3
Dense retrieval systems have proven to be effective across various benchmarks, but require substantial memory to store large search indices. Recent advances in embedding compressio…
Bridging the Semantic Gap in Virtual Machine Introspection and Forensic Memory Analysis
Christofer Fellicious, Hans P. Reiser, Michael Granitzer
Forensic Memory Analysis (FMA) and Virtual Machine Introspection (VMI) are critical tools for security in a virtualization-based approach. VMI and FMA involves using digital forens…
Malware Detection based on API calls
Christofer Fellicious, Manuel Bischof, Kevin Mayer +4
Malware attacks pose a significant threat in today's interconnected digital landscape, causing billions of dollars in damages. Detecting and identifying families as early as possib…
On the Suitability of pre-trained foundational LLMs for Analysis in German Legal Education
Lorenz Wendlinger, Christian Braun, Abdullah Al Zubaer +4
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…
SUDS: A Strategy for Unsupervised Drift Sampling
Christofer Fellicious, Lorenz Wendlinger, Mario Gancarski +2
Supervised machine learning often encounters concept drift, where the data distribution changes over time, degrading model performance. Existing drift detection methods focus on id…
DriftGAN: Using historical data for Unsupervised Recurring Drift Detection
Christofer Fellicious, Sahib Julka, Lorenz Wendlinger +1
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 predictio…
SmartKex: Machine Learning Assisted SSH Keys Extraction From The Heap Dump
Christofer Fellicious, Stewart Sentanoe, Michael Granitzer +1
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 mai…
Transfer Learning and Organic Computing for Autonomous Vehicles
Christofer Fellicious
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 w…