ProjGuard monitors agent trajectories with low-dimensional projections to cut unsafe actions from 16% to 3% and raise task completion from 59% to 65% on OS-Harm.
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2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
Supervised LDA restructuring of PCA-compressed embeddings raises silhouette separability from near zero to 0.197 in plant phenomics but yields mixed classical ML gains and persistent challenges for quantum kernel alignment under limited compute.
citing papers explorer
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ProjGuard: Safety Monitoring for Computer-Use Agents via Low-Dimensional Projections
ProjGuard monitors agent trajectories with low-dimensional projections to cut unsafe actions from 16% to 3% and raise task completion from 59% to 65% on OS-Harm.
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Supervised Latent Restructuring for Small-Data Quantum Learning in Plant Phenomics
Supervised LDA restructuring of PCA-compressed embeddings raises silhouette separability from near zero to 0.197 in plant phenomics but yields mixed classical ML gains and persistent challenges for quantum kernel alignment under limited compute.