100 citations
- Leibniz University HannoverDE89 papers
- Technische Informationsbibliothek (TIB)DE40 papers
- University of BonnDE13 papers
- GESIS - Leibniz Institute for the Social SciencesDE7 papers
- Indian Institute of Technology KharagpurIN6 papers
- University of KasselDE6 papers
- Delft University of TechnologyNL4 papers
- Freie Universität BerlinDE4 papers
- German Research Centre for Artificial IntelligenceDE4 papers
- Aalborg UniversityDK3 papers
- FIZ Karlsruhe – Leibniz Institute for Information InfrastructureDE3 papers
- FORTH Institute of Computer ScienceGR3 papers
26 papers · 1 filter
Cross-Modal Rationale Transfer for Explainable Humanitarian Classification on Social Media
Thi Huyen Nguyen, Koustav Rudra, Wolfgang Nejdl
Advances in social media data dissemination enable the provision of real-time information during a crisis. The information comes from different classes, such as infrastructure dama…
Toward Purpose-oriented Topic Model Evaluation enabled by Large Language Models
Zhiyin Tan, Jennifer D'Souza
This study presents a framework for automated evaluation of dynamically evolving topic models using Large Language Models (LLMs). Topic modeling is essential for organizing and ret…
ACCESS DENIED INC: The First Benchmark Environment for Sensitivity Awareness
Dren Fazlija, Arkadij Orlov, Sandipan Sikdar
Large language models (LLMs) are increasingly becoming valuable to corporate data management due to their ability to process text from various document formats and facilitate user…
Computational Fact-Checking of Online Discourse: Scoring scientific accuracy in climate change related news articles
Tim Wittenborg, Constantin Sebastian Tremel, Markus Stocker +1
Democratic societies need reliable information. Misinformation in popular media, such as news articles or videos, threatens to impair civic discourse. Citizens are, unfortunately,…
Beyond Accuracy: Investigating Error Types in GPT-4 Responses to USMLE Questions
Soumyadeep Roy, Aparup Khatua, Fatemeh Ghoochani +3
GPT-4 demonstrates high accuracy in medical QA tasks, leading with an accuracy of 86.70%, followed by Med-PaLM 2 at 86.50%. However, around 14% of errors remain. Additionally, curr…
GeneMask: Fast Pretraining of Gene Sequences to Enable Few-Shot Learning
Soumyadeep Roy, Jonas Wallat, Sowmya S Sundaram +2
Large-scale language models such as DNABert and LOGO aim to learn optimal gene representations and are trained on the entire Human Reference Genome. However, standard tokenization…