Unverified50% confidenceBenchmarkExact time
After introducing Feature Scope, the verified assertion output rate rose from about 20% to 95%, erroneous feature assertions dropped to 0, and model restraint reached 30/30.
1
Sources
50%
Confidence
Short-term (~14 days)
Relevance
10/13/2026
First Seen
Valid until: 10/27/2026
Sources
Related Entities
Related Claims
UnverifiedIn the experiments, the task resolution rate was 17% for zero-shot generation, 27% for generic self-correction, 23% for error-only feedback, and 90% for diagnostic counterexample feedback (A-CEGIS).77% similarUnverifiedAfter disabling schema constraints and authentication, the erroneous backend dispatch rate spiked from 0% to 95.28% in replay/test evaluations.75% similarUnverifiedIncluding specific evaluation dimensions in prompts (such as format, word count, key points to cover, and items to exclude) can improve model output quality by an average of 30%–50% compared to vague prompts.71% similarUnverifiedIn a synthetic logistic regression classifier experiment, after 80 steps of gradient-ascent-based repair, the unlearning loss rose from 0.0545 to 0.1649, yet the trigger attack success rate remained 100%.71% similarUnverifiedIn an API outage scenario with a 30% failure rate, RATED reduces the failure selection rate from 86.2% to 2.9%.70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1019278API
curl https://kongchang.com/api/v1/knowledge/claims/1019278MCP
get_claim(id=1019278)