2 citations · 2 across the 6 of their papers we have counts for
4 papers · 1 filter
Unlabeled Debiasing in Downstream Tasks via Class-wise Low Variance Regularization
Shahed Masoudian, Markus Frohmann, Navid Rekabsaz +1
Language models frequently inherit societal biases from their training data. Numerous techniques have been proposed to mitigate these biases during both the pre-training and fine-t…
Segment Any Text: A Universal Approach for Robust, Efficient and Adaptable Sentence Segmentation
Markus Frohmann, Igor Sterner, Ivan Vulić +2
Segmenting text into sentences plays an early and crucial role in many NLP systems. This is commonly achieved by using rule-based or statistical methods relying on lexical features…
Synthetic Lyrics Detection Across Languages and Genres
Yanis Labrak, Markus Frohmann, Gabriel Meseguer-Brocal +1
In recent years, the use of large language models (LLMs) to generate music content, particularly lyrics, has gained in popularity. These advances provide valuable tools for artists…
What the Weight?! A Unified Framework for Zero-Shot Knowledge Composition
Carolin Holtermann, Markus Frohmann, Navid Rekabsaz +1
The knowledge encapsulated in a model is the core factor determining its final performance on downstream tasks. Much research in NLP has focused on efficient methods for storing an…