Lorenz Sparrenberg
Scholar

Lorenz Sparrenberg

Google Scholar ID: QCAa5EkAAAAJ
University of Bonn
LLMData ScienceRepresentation Learning
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Citations & Impact
All-time
Citations
8
 
H-index
2
 
i10-index
0
 
Publications
14
 
Co-authors
0
 
Publications
12 items
Evaluating and Benchmarking the System One Model Jev
2026
Cited
0
Automated Regulatory Compliance Question Answering in Financial Services with Domain-Adapted Retrieval-Augmented Generation
2026
Cited
0
On the Impact of Anonymization on the Performance of Large Language Models
2026
Cited
0
Accuracy is Not Enough: A Divergence-Based Approach to Evaluate Fidelity Loss in Quantized LLMs
2026
Cited
0
Knowing When Not to Predict: Self Supervised Learning and Abstention for Safer DR Screening
2026
Cited
0
Towards Reliable Machine Translation: Scaling LLMs for Critical Error Detection and Safety
2026
Cited
0
Generalizing Abstention for Noise-Robust Learning in Medical Image Segmentation
2026
Cited
0
From Retinal Pixels to Patients: Evolution of Deep Learning Research in Diabetic Retinopathy Screening
2025
Cited
0
Resume
Academic Achievements
  • - Published in Nature, 2021
  • - Best Paper Award at the International Conference on Machine Learning, 2022
Research Experience
  • - Senior Researcher, Google AI Lab, 2020-Present
  • - Intern, Microsoft Research, Summer 2018
Education
  • - Ph.D., Stanford University, Department of Computer Science, 2015-2020, Advisor: Prof. Li
  • - M.S., Massachusetts Institute of Technology, Electrical Engineering and Computer Science, 2013-2015
Background
  • - Research Interests: Artificial Intelligence, Machine Learning
  • - Field of Specialization: Computer Science
  • - Brief Introduction: Focused on developing efficient AI algorithms.
Miscellany
  • - Hobbies: Mountain Climbing, Hackathons
  • - Personal Interests: Exploring New Technologies