3 citations · 5 across the 8 of their papers we have counts for
9 papers
Toward Generalized Cross-Lingual Hateful Language Detection with Web-Scale Data and Ensemble LLM Annotations
Dang H. Dang, Jelena Mitrovi, Michael Granitzer
We study whether large-scale unlabelled web data and LLM-based synthetic annotations can improve multilingual hate speech detection. Starting from texts crawled via OpenWebSearch.e…
Robust Generalizable Heterogeneous Legal Link Prediction
Lorenz Wendlinger, Simon Alexander Nonn, Abdullah Al Zubaer +1
Recent work has applied link prediction to large heterogeneous legal citation networks \new{with rich meta-features}. We find that this approach can be improved by including edge d…
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…
Enhancing Rhetorical Figure Annotation: An Ontology-Based Web Application with RAG Integration
Ramona Kühn, Jelena Mitrović, Michael Granitzer
Rhetorical figures play an important role in our communication. They are used to convey subtle, implicit meaning, or to emphasize statements. We notice them in hate speech, fake ne…
Krony-PT: GPT2 compressed with Kronecker Products
Mohamed Ayoub Ben Ayad, Jelena Mitrovic, Michael Granitzer
We introduce Krony-PT, a compression technique for GPT-2 based on Kronecker products. We specifically target the feed-forward weights of each transformer block, and systematically…
Towards an Improved Metric for Evaluating Disentangled Representations
Sahib Julka, Yashu Wang, Michael Granitzer
Disentangled representation learning plays a pivotal role in making representations controllable, interpretable and transferable. Despite its significance in the domain, the quest…
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…
Challenges and Considerations in Annotating Legal Data: A Comprehensive Overview
Harshil Darji, Jelena Mitrović, Michael Granitzer
The process of annotating data within the legal sector is filled with distinct challenges that differ from other fields, primarily due to the inherent complexities of legal languag…
LLMs in the Loop: Leveraging Large Language Model Annotations for Active Learning in Low-Resource Languages
Nataliia Kholodna, Sahib Julka, Mohammad Khodadadi +2
Low-resource languages face significant barriers in AI development due to limited linguistic resources and expertise for data labeling, rendering them rare and costly. The scarcity…