GAIR Paper 111 | 谁动了我的大模型？IJCAI 2026最新综述揭秘大模型“隐式身份”防伪战
Merged summary
TL;DR - An IJCAI 2026 survey unifies LLM fingerprinting and watermarking under an “implicit identity” framework for protecting datasets, models, and generated content. It supports ownership verification, misuse detection, and provenance tracing.
- Fingerprints extract intrinsic signals; watermarks deliberately embed verifiable signals.
- The taxonomy spans datasets, models, and generated text, using similarity-based attribution or key-based verification.
- Evaluation covers claim correctness, benign-transformation robustness, adaptive attacks, and deployment cost.
- Key challenges include preserving model utility, surviving model or content transformations, and reducing verification overhead.
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GAIR Paper 111 | 谁动了我的大模型？IJCAI 2026最新综述揭秘大模型“隐式身份”防伪战
TL;DR - An IJCAI 2026 survey unifies LLM fingerprinting and watermarking under an “implicit identity” framework for protecting datasets, models, and generated content. It supports ownership verification, misuse detection, and provenance tracing.
- Fingerprints extract intrinsic signals; watermarks deliberately embed verifiable signals.
- The taxonomy spans datasets, models, and generated text, using similarity-based attribution or key-based verification.
- Evaluation covers claim correctness, benign-transformation robustness, adaptive attacks, and deployment cost.
- Key challenges include preserving model utility, surviving model or content transformations, and reducing verification overhead.