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Diverse Word Choices, Same Reference: Annotating Lexically-Rich Cross-Document Coreference
Anastasia Zhukova, Felix Hamborg, Karsten Donnay +2
Cross-document coreference resolution (CDCR) identifies and links mentions of the same entities and events across related documents, enabling content analysis that aggregates infor…
Piecing Together Cross-Document Coreference Resolution Datasets: Systematic Dataset Analysis and Unification
Anastasia Zhukova, Terry Ruas, Jan Philip Wahle +1
Research in CDCR remains fragmented due to heterogeneous dataset formats, varying annotation standards, and the predominance of the CDCR definition as the event coreference resolut…
Contrastive Learning Using Graph Embeddings for Domain Adaptation of Language Models in the Process Industry
Anastasia Zhukova, Jonas Lührs, Christian E. Lobmüller +1
Recent trends in NLP utilize knowledge graphs (KGs) to enhance pretrained language models by incorporating additional knowledge from the graph structures to learn domain-specific t…
What's in the News? Towards Identification of Bias by Commission, Omission, and Source Selection (COSS)
Anastasia Zhukova, Terry Ruas, Felix Hamborg +2
In a world overwhelmed with news, determining which information comes from reliable sources or how neutral is the reported information in the news articles poses a challenge to new…
Link Prediction for Event Logs in the Process Industry
Anastasia Zhukova, Thomas Walton, Christian E. Lobmüller +1
In the era of graph-based retrieval-augmented generation (RAG), link prediction is a significant preprocessing step for improving the quality of fragmented or incomplete domain-spe…
Efficient Domain-adaptive Continual Pretraining for the Process Industry in the German Language
Anastasia Zhukova, Christian E. Matt, Bela Gipp
Domain-adaptive continual pretraining (DAPT) is a state-of-the-art technique that further trains a language model (LM) on its pretraining task, e.g., masked language modeling (MLM)…
Automated Collection of Evaluation Dataset for Semantic Search in Low-Resource Domain Language
Anastasia Zhukova, Christian E. Matt, Bela Gipp
Domain-specific languages that use a lot of specific terminology often fall into the category of low-resource languages. Collecting test datasets in a narrow domain is time-consumi…
Generative User-Experience Research for Developing Domain-specific Natural Language Processing Applications
Anastasia Zhukova, Lukas von Sperl, Christian E. Matt +1
User experience (UX) is a part of human-computer interaction (HCI) research and focuses on increasing intuitiveness, transparency, simplicity, and trust for the system users. Most…
ANEA: Automated (Named) Entity Annotation for German Domain-Specific Texts
Anastasia Zhukova, Felix Hamborg, Bela Gipp
Named entity recognition (NER) is an important task that aims to resolve universal categories of named entities, e.g., persons, locations, organizations, and times. Despite its com…
XCoref: Cross-document Coreference Resolution in the Wild
Anastasia Zhukova, Felix Hamborg, Karsten Donnay +1
Datasets and methods for cross-document coreference resolution (CDCR) focus on events or entities with strict coreference relations. They lack, however, annotating and resolving co…
Towards Evaluation of Cross-document Coreference Resolution Models Using Datasets with Diverse Annotation Schemes
Anastasia Zhukova, Felix Hamborg, Bela Gipp
Established cross-document coreference resolution (CDCR) datasets contain event-centric coreference chains of events and entities with identity relations. These datasets establish…