Jev 1.14

TypeSafe AI · released Oct 14, 2026

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Openness taxonomy

access, licence, and disclosure — never a single open/closed binary

raw values as extracted — free text, never inferred from branding

as reported — vendor-supplied unless otherwise noted

No benchmark data on this release yet.

from the assessed source item, when one is linked

Impact: lowConfidence: lowNat-sec: noneindependent reporting

Evidence limitations: A single press report provides limited detail and no independent evaluation of the new features.

from paper_model_links

Just Ask Jev: Reinforcement Learning for Calibrated Decisions as a Zero-Shot Detector of AI Alignment Failuresevaluates · 99% confidence
LAVOIR: Teaching a Single-Pass Decision Encoder When and What to Ask with Amortized Value of Informationrelated · 90% confidence
More Features Are Not More Evidence: Limits of Training-Free Human Activity Recognition with Jevevaluates · 100% confidence
Beyond Answer Confidence: A Controlled Audit of Self-Knowledge in a Black-Box Decision Modelevaluates · 100% confidence
Fast Models, Slow Evidence: A Paired and Self-Audited Evaluation of System-1 Decision Models for LLM Agent Harnessesevaluates · 100% confidence
TypedBench: A Benchmark for Calibration, Framing Sensitivity, and Cost in System One Decision Modelsrelated · 55% confidence
When Faster Decisions Do Not Make Better Agents: An Empirical Study of Jev in Agent Workflowsevaluates · 99% confidence
The World Won't Wait: Evaluating and Teaching Agents Under a Live Clock