PIIGuard uses optimized hidden HTML fragments on webpages to block LLMs from leaking contact PII via indirect prompt injection, achieving at least 97% defense success across tested models while preserving benign QA utility.
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NPSolver trains neural Poisson solvers label-free by supervising with a small number of preconditioned conjugate gradient steps and adds Boundary-Aware Transolver for mixed boundaries, outperforming baselines on 2D/3D irregular geometries.
A differentially private pipeline using node-level DP summaries to fit ERGMs or SBMs, generate synthetic networks, and simulate SIS disease spread on ARTNet sexual contact data produces incidence, prevalence, and intervention effect sizes close to non-private versions.
NSHA improves LLM handling of hierarchical instruction conflicts by combining solver-guided constraint satisfaction at inference with distillation of those decisions into model parameters at training.
citing papers explorer
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PIIGuard: Mitigating PII Harvesting under Adversarial Sanitization
PIIGuard uses optimized hidden HTML fragments on webpages to block LLMs from leaking contact PII via indirect prompt injection, achieving at least 97% defense success across tested models while preserving benign QA utility.
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Differentially Private Modeling of Disease Transmission within Human Contact Networks
A differentially private pipeline using node-level DP summaries to fit ERGMs or SBMs, generate synthetic networks, and simulate SIS disease spread on ARTNet sexual contact data produces incidence, prevalence, and intervention effect sizes close to non-private versions.