13 citations · 13 across the 2 of their papers we have counts for
2 papers
cs.CL2025
Resource-Efficient Adaptation of Large Language Models for Text Embeddings via Prompt Engineering and Contrastive Fine-tuning
Benedikt Roth, Stephan Rappensperger, Tianming Qiu +3
Large Language Models (LLMs) have become a cornerstone in Natural Language Processing (NLP), achieving impressive performance in text generation. Their token-level representations…
cs.CV2024★ 13 cited
Low-resource finetuning of foundation models beats state-of-the-art in histopathology
Benedikt Roth, Valentin Koch, Sophia J. Wagner +3
To handle the large scale of whole slide images in computational pathology, most approaches first tessellate the images into smaller patches, extract features from these patches, a…