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Evoflux transforms how compact agents navigate tool workflows, boosting execution success rates from a mere 3% to up to 24% in real-world scenarios.
Hallucinations in multi-agent LLM workflows are far more complex and frequent than previously measured, with nearly half involving multiple types simultaneously, demanding a shift from final-answer checks to trajectory-aware auditing.
Neurosymbolic grounding of LLMs in telemetry and knowledge graphs slashes expert-rated overclaims in industrial maintenance explanations by 93%, making AI assistants far more trustworthy in safety-critical settings.
