4 citations · 4 across the 8 of their papers we have counts for
4 papers · 1 filter
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…
Mixture of Modular Experts: Distilling Knowledge from a Multilingual Teacher into Specialized Modular Language Models
Mohammed Al-Maamari, Mehdi Ben Amor, Michael Granitzer
This research combines Knowledge Distillation (KD) and Mixture of Experts (MoE) to develop modular, efficient multilingual language models. Key objectives include evaluating adapti…
Beyond Benchmarks: Evaluating Embedding Model Similarity for Retrieval Augmented Generation Systems
Laura Caspari, Kanishka Ghosh Dastidar, Saber Zerhoudi +2
The choice of embedding model is a crucial step in the design of Retrieval Augmented Generation (RAG) systems. Given the sheer volume of available options, identifying clusters of…
Computational Approaches to the Detection of Lesser-Known Rhetorical Figures: A Systematic Survey and Research Challenges
Ramona Kühn, Jelena Mitrović, Michael Granitzer
Rhetorical figures play a major role in our everyday communication as they make text more interesting, more memorable, or more persuasive. Therefore, it is important to computation…