Tag: agentic AI safety
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Robust Global-Local Fusion for Autonomous Driving with LiDAR Errors
Explore robust global-local command fusion for autonomous driving under LiDAR errors, enhancing safety and navigation with continuous control arbitration.
Enhancing Safety in Vision-Language Models with CARE Framework
Discover how the CARE framework uses causal discovery and dual-modal projection to diagnose and repair unsafe channels in vision-language models.
SafetyDrift: Predicting AI Safety Violations Before They Happen
Discover how SafetyDrift predicts when AI agents might cross safety lines, enabling proactive monitoring to prevent data leaks and violations.
Anthropic AI Safety Errors Spark Industry Debate
Anthropic faces AI safety challenges due to human error, prompting calls for stronger oversight and transparency in AI development.
Squish and Release: Reducing AI Hallucinations Effectively
Discover how Squish and Release architecture detects and reduces hidden AI hallucinations, improving language model safety and reliability.