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RongHua Li

4 accepted papers

2026

Class-feature Watermark: A Resilient Black-box Watermark Against Model Extraction Attacks

AAAI 2026technical

Machine learning models constitute valuable intellectual property, yet remain vulnerable to model extraction attacks (MEA), where adversaries replicate their functionality through black-box queries. Model watermarking counters MEAs by embedding forensic markers for ownership verification. Current bl

Cited by 0SourcePDFScholar
2025

Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?

ICML 2025poster

Low rank adaptation (LoRA) has emerged as a prominent technique for fine-tuning large language models (LLMs) thanks to its superb efficiency gains over previous methods. While extensive studies have examined the performance and structural properties of LoRA, its behavior upon training-time attacks r…

2025

“Yes, My LoRD.” Guiding Language Model Extraction with Locality Reinforced Distillation

ACL 2025long

Model extraction attacks (MEAs) on large language models (LLMs) have received increasing attention in recent research. However, existing attack methods typically adapt the extraction strategies originally developed for deep neural networks (DNNs). They neglect the underlying inconsistency between th…