GuardMCP - Deterministic Runtime Semantic Enforcement for Agentic Tool Execution using Directional Intent–Action Alignment
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Updated
Apr 4, 2026 - Python
GuardMCP - Deterministic Runtime Semantic Enforcement for Agentic Tool Execution using Directional Intent–Action Alignment
A research-grade PyTorch framework for robust object recognition under extreme environmental noise. Implements self-supervised Denoising Autoencoders (DAE) with ResNet/ViT architectures on the official CIFAR-10-C benchmark. Includes Grad-CAM interpretability and automated robustness benchmarking.
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