4 papers
SynBench: A Benchmark for Differentially Private Text Generation
Yidan Sun, Viktor Schlegel, Srinivasan Nandakumar +9
Synthetic text generation with Differential Privacy (DP) guarantees emerges as a principled approach that can enable the sharing of sensitive datasets across institutional and regu…
Privacy-Preserving Generation of Clinical Narratives from Medical Terminologies
Yuping Wu, Viktor Schlegel, Warren Del-Pinto +11
In high-stakes domains such as healthcare, privacy concerns severely limit the use of real-world training data. Differentially private (DP) synthetic data offers a promising altern…
Evaluating Differentially Private Generation of Domain-Specific Text
Yidan Sun, Viktor Schlegel, Srinivasan Nandakumar +7
Generative AI offers transformative potential for high-stakes domains such as healthcare and finance, yet privacy and regulatory barriers hinder the use of real-world data. To addr…
Which Side Are You On? A Multi-task Dataset for End-to-End Argument Summarisation and Evaluation
Hao Li, Yuping Wu, Viktor Schlegel +8
With the recent advances of large language models (LLMs), it is no longer infeasible to build an automated debate system that helps people to synthesise persuasive arguments. Previ…