1 citations · 2 across the 8 of their papers we have counts for
8 papers
PQFed: A Privacy-Preserving Quality-Controlled Federated Learning Framework
Weiqi Yue, Wenbiao Li, Yuzhou Jiang +3
Federated learning enables collaborative model training without sharing raw data, but data heterogeneity consistently challenges the performance of the global model. Traditional op…
Watermarking Without Standards Is Not AI Governance
Alexander Nemecek, Yuzhou Jiang, Erman Ayday
Watermarking has emerged as a leading technical proposal for attributing generative AI content and is increasingly cited in global governance frameworks. This position paper argues…
The Feasibility of Topic-Based Watermarking on Academic Peer Reviews
Alexander Nemecek, Yuzhou Jiang, Erman Ayday
Large language models (LLMs) are increasingly integrated into academic workflows, with many conferences and journals permitting their use for tasks such as language refinement and…
Validating GWAS Findings through Reverse Engineering of Contingency Tables
Yuzhou Jiang, Erman Ayday
Reproducibility in genome-wide association studies (GWAS) is crucial for ensuring reliable genomic research outcomes. However, limited access to original genomic datasets (mainly d…
Privacy-Preserving Collaborative Genomic Research: A Real-Life Deployment and Vision
Zahra Rahmani, Nahal Shahini, Nadav Gat +7
The data revolution holds significant promise for the health sector. Vast amounts of data collected from individuals will be transformed into knowledge, AI models, predictive syste…
Topic-Based Watermarks for Large Language Models
Alexander Nemecek, Yuzhou Jiang, Erman Ayday
The indistinguishability of large language model (LLM) output from human-authored content poses significant challenges, raising concerns about potential misuse of AI-generated text…
PROVGEN: A Privacy-Preserving Approach for Outcome Validation in Genomic Research
Yuzhou Jiang, Tianxi Ji, Erman Ayday
As genomic research has grown increasingly popular in recent years, dataset sharing has remained limited due to privacy concerns. This limitation hinders the reproducibility and va…
Robust Fingerprint of Location Trajectories Under Differential Privacy
Yuzhou Jiang, Emre Yilmaz, Erman Ayday
Directly releasing those data raises privacy and liability (e.g., due to unauthorized distribution of such datasets) concerns since location data contain users' sensitive informati…