collaborators

5 papers

cs.CY2026

Who Gets Flagged? The Pluralistic Evaluation Gap in AI Content Watermarking

Alexander Nemecek, Osama Zafar, Yuqiao Xu +2

Watermarking is becoming the default mechanism for AI content authentication, with governance policies and frameworks referencing it as infrastructure for content provenance. Yet a…

cs.LG2026

Privacy Policy Enforcement Guardrails for Data-Sensitive Retrieval-Augmented Generation

Osama Zafar, Alexander Nemecek, Yiqian Zhang +5

Standard PII filters often miss contextual data leakage in RAG systems, such as non-regulated attribute clusters that collectively identify individuals. We introduce a Privacy Poli…

cs.LG2026

Quantifying Memorization and Privacy Risks in Genomic Language Models

Alexander Nemecek, Wenbiao Li, Xiaoqian Jiang +2

Genomic language models (GLMs) have emerged as powerful tools for learning representations of DNA sequences, enabling advances in variant prediction, regulatory element identificat…

cs.LG2025

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…

cs.LG2025

Privacy-Preserving Model and Preprocessing Verification for Machine Learning

Wenbiao Li, Anisa Halimi, Xiaoqian Jiang +2

This paper presents a framework for privacy-preserving verification of machine learning models, focusing on models trained on sensitive data. Integrating Local Differential Privacy…