3 citations · 5 across the 3 of their papers we have counts for
5 papers
Training-Data Extraction from Genomic Language Models
Tianhao Mao, Zihao Wang, Dongfang Zhao +3
Genomic language models generate long nucleotide continuations from short prefixes, exposing a direct route for studying training-sequence extraction through the generation interfa…
Hey, That's My Data! Token-Only Dataset Inference in Large Language Models
Chen Xiong, Zihao Wang, Rui Zhu +4
Large Language Models (LLMs) rely on massive training datasets, often including proprietary data, which raises concerns about unauthorized usage and copyright infringement. Existin…
Enhancing Patient-Centric Communication: Leveraging LLMs to Simulate Patient Perspectives
Xinyao Ma, Rui Zhu, Zihao Wang +5
Large Language Models (LLMs) have demonstrated impressive capabilities in role-playing scenarios, particularly in simulating domain-specific experts using tailored prompts. This ab…
ByzSFL: Achieving Byzantine-Robust Secure Federated Learning with Zero-Knowledge Proofs
Yongming Fan, Rui Zhu, Zihao Wang +5
The advancement of AI models, especially those powered by deep learning, faces significant challenges in data-sensitive industries like healthcare and finance due to the distribute…
DPAdapter: Improving Differentially Private Deep Learning through Noise Tolerance Pre-training
Zihao Wang, Rui Zhu, Dongruo Zhou +4
Recent developments have underscored the critical role of \textit{differential privacy} (DP) in safeguarding individual data for training machine learning models. However, integrat…