Model extraction
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Benchmarks
UML Classes With Specs
Most implemented
FedRolex: Model-Heterogeneous Federated Learning with Rolling Sub-Model Extraction
Entangled Watermarks as a Defense against Model Extraction
"Yes, My LoRD." Guiding Language Model Extraction with Locality Reinforced Distillation
Protecting Language Generation Models via Invisible Watermarking
Process Extraction from Text: Benchmarking the State of the Art and Paving the Way for Future Challenges
Data-Free Model Extraction
Papers
JudgeStealer: Extracting LLM Judging Capabilities across Evaluation Protocols
Large language model (LLM) judges are increasingly used across various evaluation scenarios, making their judgment capabilities valuable intellectual property. However, black-box access exposes these capabilities to mode…
Model extractionCaliber: Cross-Architecture Extraction-Cost Control for Score-Returning APIs
We present Caliber, an output-perturbation defense against model extraction that formulates noise selection as a calibration problem: how much the defense degrades the supervision signal used to train a surrogate, and th…
Knowledge DistillationModel extractionDECODEM: Data Extraction from Corporate Organizational Documents via Enhanced Methods
Much empirical legal research depends on translating unstructured text into structured variables. In corporate governance research as elsewhere, this translation has traditionally relied on human coding of documents such…
Binary ClassificationModel extractionLet Them Steal: Trapping Large Language Model Extraction Attacks with Knowledge Honeypot
Large language models deployed as commercial APIs are vulnerable to model extraction attacks, while existing defenses either act too late or degrade utility for legitimate users. We propose \textbf{Knowledge Trap}, a def…
Model extractionSciR: A Controllable Benchmark for Scientific Reasoning in LLMs
Three paradigmatic forms of inference recur across scientific reasoning: deduction, induction, and causal abduction. Reliably evaluating LLMs on these in scientific settings is currently out of reach: scientific benchmar…
Model extractionT2S: A Rehearsal-Based Approach for Extraction-Resistant Model Watermarking
Model watermarking safeguards AI model intellectual property by embedding distinctive knowledge that induces unique behavioral signatures. The primary technical challenge lies in ensuring watermark robustness against var…
Model extraction