SOTAVerified

Model extraction

Model extraction attacks, aka model stealing attacks, are used to extract the parameters from the target model. Ideally, the adversary will be able to steal and replicate a model that will have a very similar performance to the target model.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1–10 of 176 papers

TitleStatusHype
Safety at Scale: A Comprehensive Survey of Large Model SafetyCode3
MARLeME: A Multi-Agent Reinforcement Learning Model Extraction LibraryCode1
Are You Copying My Model? Protecting the Copyright of Large Language Models for EaaS via Backdoor WatermarkCode1
Data-Free Model ExtractionCode1
"Yes, My LoRD." Guiding Language Model Extraction with Locality Reinforced DistillationCode1
FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model ExtractionCode1
Black-Box Attacks on Sequential Recommenders via Data-Free Model ExtractionCode1
ATOM: A Framework of Detecting Query-Based Model Extraction Attacks for Graph Neural NetworksCode1
Cryptanalytic Extraction of Neural Network ModelsCode1
Entangled Watermarks as a Defense against Model ExtractionCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1three-step-originalExact Match0.17—Unverified