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Found 12 papers, 4 papers with code
GRhOOT: Ontology of Rhetorical Figures in German
GRhOOT, the German RhetOrical OnTology, is a domain ontology of 110 rhetorical figures in the German language.
Multi-word Expressions for Abusive Speech Detection in Serbian
This paper presents our work on the refinement and improvement of the Serbian language part of Hurtlex, a multilingual lexicon of words to hurt.
WebFAQ: A Multilingual Collection of Natural Q&A Datasets for Dense Retrieval
These datasets are carefully curated through refined filtering and near-duplicate detection, yielding high-quality resources for training and evaluating multilingual dense retrieval models.
Enhancing Rhetorical Figure Annotation: An Ontology-Based Web Application with RAG Integration
To overcome this issue, we develop a web application called "Find your Figure" that facilitates the identification and annotation of German rhetorical figures.
Challenges and Considerations in Annotating Legal Data: A Comprehensive Overview
This paper provides an expanded view of these challenges and aims to offer a foundational understanding and guidance for researchers and professionals engaged in legal data annotation projects.
Computational Approaches to the Detection of Lesser-Known Rhetorical Figures: A Systematic Survey and Research Challenges
Rhetorical figures play a major role in our everyday communication as they make text more interesting, more memorable, or more persuasive.
Technical Report: Impact of Position Bias on Language Models in Token Classification
Therefore, we conduct an in-depth evaluation of the impact of position bias on the performance of LMs when fine-tuned on token classification benchmarks.
A Benchmark of PDF Information Extraction Tools using a Multi-Task and Multi-Domain Evaluation Framework for Academic Documents
Using the new framework, we benchmark ten freely available tools in extracting document metadata, bibliographic references, tables, and other content elements from academic PDF documents.
German BERT Model for Legal Named Entity Recognition
Even though there is much research done on NER using BERT and other popular language models, the same is not explored in detail when it comes to Legal NLP or Legal Tech.
Exploiting Transformer-based Multitask Learning for the Detection of Media Bias in News Articles
Media has a substantial impact on the public perception of events.
HateBERT: Retraining BERT for Abusive Language Detection in English
In this paper, we introduce HateBERT, a re-trained BERT model for abusive language detection in English.
Ranked #1 on
Hate Speech Detection
on AbusEval
