2 citations · 2 across the 4 of their papers we have counts for
4 papers
Unintended Memorization of Sensitive Information in Fine-Tuned Language Models
Marton Szep, Jorge Marin Ruiz, Georgios Kaissis +4
Fine-tuning Large Language Models (LLMs) on sensitive datasets carries a substantial risk of unintended memorization and leakage of Personally Identifiable Information (PII), which…
Modeling Challenging Patient Interactions: LLMs for Medical Communication Training
Anna Bodonhelyi, Christian Stegemann-Philipps, Alessandra Sonanini +6
Effective patient communication is pivotal in healthcare, yet traditional medical training often lacks exposure to diverse, challenging interpersonal dynamics. To bridge this gap,…
Fine-tuning Large Language Models with Limited Data: A Survey and Practical Guide
Marton Szep, Daniel Rueckert, Rüdiger von Eisenhart-Rothe +1
Fine-tuning large language models (LLMs) with limited data poses a practical challenge in low-resource languages, specialized domains, and constrained deployment settings. While pr…
Reinforcement Learning for Solving Robotic Reaching Tasks in the Neurorobotics Platform
Marton Szep, Leander Lauenburg, Kevin Farkas +2
In recent years, reinforcement learning (RL) has shown great potential for solving tasks in well-defined environments like games or robotics. This paper aims to solve the robotic r…