339 citations
- University of PotsdamDE102 papers
- Karlsruhe Institute of TechnologyDE9 papers
- Technische Universität BerlinDE8 papers
- École PolytechniqueFR6 papers
- Humboldt-Universität zu BerlinDE6 papers
- Icahn School of Medicine at Mount SinaiUS5 papers
- Laboratoire d'Informatique de l'École PolytechniqueFR5 papers
- The University of AdelaideAU5 papers
- University of TwenteNL5 papers
- Centre National de la Recherche ScientifiqueFR4 papers
- Institut Polytechnique de ParisFR4 papers
- Charité - Universitätsmedizin BerlinDE3 papers
9 papers · 1 filter
Segmentation and Processing of German Court Decisions from Open Legal Data
Harshil Darji, Martin Heckelmann, Christina Kratsch +1
The availability of structured legal data is important for advancing Natural Language Processing (NLP) techniques for the German legal system. One of the most widely used datasets,…
ReFACT: A Benchmark for Scientific Confabulation Detection with Positional Error Annotations
Yindong Wang, Martin Preiß, Margarita Bugueño +4
The mechanisms underlying scientific confabulation in Large Language Models (LLMs) remain poorly understood. We introduce ReFACT (Reddit False And Correct Texts), a benchmark of 1,…
xMEN: A Modular Toolkit for Cross-Lingual Medical Entity Normalization
Florian Borchert, Ignacio Llorca, Roland Roller +2
Objective: To improve performance of medical entity normalization across many languages, especially when fewer language resources are available compared to English. Materials and M…
Large-Scale Evaluation of Topic Models and Dimensionality Reduction Methods for 2D Text Spatialization
Daniel Atzberger, Tim Cech, Willy Scheibel +4
Topic models are a class of unsupervised learning algorithms for detecting the semantic structure within a text corpus. Together with a subsequent dimensionality reduction algorith…
Connecting the Dots: What Graph-Based Text Representations Work Best for Text Classification Using Graph Neural Networks?
Margarita Bugueño, Gerard de Melo
Given the success of Graph Neural Networks (GNNs) for structure-aware machine learning, many studies have explored their use for text classification, but mostly in specific domains…
FOCUS: Effective Embedding Initialization for Monolingual Specialization of Multilingual Models
Konstantin Dobler, Gerard de Melo
Using model weights pretrained on a high-resource language as a warm start can reduce the need for data and compute to obtain high-quality language models for other, especially low…