12 citations · 33 across the 25 of their papers we have counts for
7 papers · 1 filter
Token-Level Graphs for Short Text Classification
Gregor Donabauer, Udo Kruschwitz
The classification of short texts is a common subtask in Information Retrieval (IR). Recent advances in graph machine learning have led to interest in graph-based approaches for lo…
BioRAGent: A Retrieval-Augmented Generation System for Showcasing Generative Query Expansion and Domain-Specific Search for Scientific Q&A
Samy Ateia, Udo Kruschwitz
We present BioRAGent, an interactive web-based retrieval-augmented generation (RAG) system for biomedical question answering. The system uses large language models (LLMs) for query…
The AI Interface: Designing for the Ideal Machine-Human Experience (Editorial)
Aparna Sundar, Tony Russell-Rose, Udo Kruschwitz +1
As artificial intelligence (AI) becomes increasingly embedded in daily life, designing intuitive, trustworthy, and emotionally resonant AI-human interfaces has emerged as a critica…
Modeling Social Media Recommendation Impacts Using Academic Networks: A Graph Neural Network Approach
Sabrina Guidotti, Gregor Donabauer, Simone Somazzi +3
The widespread use of social media has highlighted potential negative impacts on society and individuals, largely driven by recommendation algorithms that shape user behavior and s…
Can Open-Source LLMs Compete with Commercial Models? Exploring the Few-Shot Performance of Current GPT Models in Biomedical Tasks
Samy Ateia, Udo Kruschwitz
Commercial large language models (LLMs), like OpenAI's GPT-4 powering ChatGPT and Anthropic's Claude 3 Opus, have dominated natural language processing (NLP) benchmarks across diff…
Investigating Neural Machine Translation for Low-Resource Languages: Using Bavarian as a Case Study
Wan-Hua Her, Udo Kruschwitz
Machine Translation has made impressive progress in recent years offering close to human-level performance on many languages, but studies have primarily focused on high-resource la…
Challenges in Pre-Training Graph Neural Networks for Context-Based Fake News Detection: An Evaluation of Current Strategies and Resource Limitations
Gregor Donabauer, Udo Kruschwitz
Pre-training of neural networks has recently revolutionized the field of Natural Language Processing (NLP) and has before demonstrated its effectiveness in computer vision. At the…