3 papers
cs.CR2026
PromptGraph: Graph-Guided Prompt Sanitization for Balancing Privacy and Utility in LLM Inference
Chen Gu, Hui Wan, Donghui Hu +2
Large Language Model (LLM) services introduce a fundamental privacy challenge. Sensitive information may be inferred not only from explicit identifiers, such as names or phone numb…
cs.LG2025
FLClear: Visually Verifiable Multi-Client Watermarking for Federated Learning
Chen Gu, Yingying Sun, Yifan She +1
Federated learning (FL) enables multiple clients to collaboratively train a shared global model while preserving the privacy of their local data. Within this paradigm, the intellec…
cs.CR2025
Modification and Generated-Text Detection: Achieving Dual Detection Capabilities for the Outputs of LLM by Watermark
Yuhang Cai, Yaofei Wang, Donghui Hu +1
The development of large language models (LLMs) has raised concerns about potential misuse. One practical solution is to embed a watermark in the text, allowing ownership verificat…