UltraGuard watermarks face videos in real time using ultrasound biometrics
Smartphone ultrasound and video motion are fused into watermarks meant to survive forgery and editing.
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Smartphone ultrasound and video motion are fused into watermarks meant to survive forgery and editing.
Across three domains, six models and three frameworks, owner verification reached 99.2% and buyer Top-1 attribution 99.3%.
Logit Laundering manipulates model outputs at inference time using logit reshaping to suppress watermark signals while preserving model utility on downstream tasks.
NotaryMark aligns watermarks with diffusion latent denoising for robust black-box auditing across datasets and models.
RL policy balances watermark energy against control distortion on UR5 robot.
Averaging only two personalized audio copies produces tracing-failure rates of 87.7-99.7% while largely preserving audio quality.
ScrambleMark achieves 97% evasion on commercial platforms while preserving speech naturalness at 4.2/5.
SHield embeds payloads in 4DGS via SH coefficient perturbation for decoder-free ownership verification.
PP-Mark anchors statistical detection to zero-knowledge proofs to ensure unforgeability against forgeries.
Authors report a scalable 32–128-bit payload, a 94.6% decode rate against CtrlRegen+, and 98.8% forgery detection.
A trusted verifier checks a disputed trajectory without rerunning the agent, using wrong-key calibration and abstention.
At a 0.1% false-positive rate it detected 79% of distilled models at n-gram=1, versus 29% for a token baseline.
After copy-paste strips invisible characters, detection needs about 2 English or Persian code points but 93 Lao.
After full identifier renaming, BitAcc stays at 82.27% on CodeLlama and 83.77% on DeepSeek-Coder.
With 32 bits in 300 tokens, authors report 90.01% extraction accuracy after paraphrasing while preserving text quality.
Tests on two federated-learning schemes strip ownership marks without training data and with little accuracy loss.
A trusted auditor enrolls identities in advance; audit time uses only the claimed identity and the released summary, not provider logs.
On OPT-1.3B and other open-weight models, BLADE beat compared detectors across modes and substitutions.
Legacy-chain training plus angular diversity loss makes neural audio watermarks backward compatible.
Provenance marks in leaked agent harnesses mostly fail when a self-evolving LLM rewrites the marked code.
SkillMarker watermarks agent skills with KGW so owners can verify copies without breaking procedural accuracy.
ECGWmark watermarks ECG signals without quantization and keeps over 90% bit accuracy under circular shifts.
WaveMark watermarks diffusion noise in the wavelet domain and keeps over 88% accuracy under removal attacks.
SemField embeds a training-free linear semantic watermark in sentence embeddings and beats 12 baselines under paraphrase attacks.
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