VeriTrail: Detect hallucination and trace provenance in AI workflows
Dasha Metropolitansky, Research Data Scientist, Microsoft Research Special Projects, introduces VeriTrail, a new method for closed-domain hallucination detection in multi-step AI workflows. Unlike prior methods, VeriTrail provides traceability: it identifies where hallucinated content was likely…
VeriTrail: Detecting hallucination and tracing provenance in multi-step AI workflows
VeriTrail, new from Microsoft Research, can detect AI-generated content that is not supported by the source text, trace the provenance of content from final output back to the source, and locate where errors were likely…
Project Ire autonomously identifies malware at scale
Designed to classify software without context, Project Ire replicates the gold standard in malware analysis through reverse engineering. It streamlines a complex, expert-driven process, making large-scale malware detection faster & more consistent.
Project Ire
Autonomous malware classification Malware classification is one of cybersecurity’s hardest unsolved problems. Suspicious files arrive faster than analysts can clear them, and the gold standard for a verdict is full behavioral reverse engineering: slow, expensive,…