Unverified50% confidenceBenchmarkExact time
ADE's self-test benchmark shows: average latency 0.18 ms/decision, latency range 0.07–0.29 ms, average confidence 0.533, average margin 0.275, and 1–2 triggered rules per decision.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/12/2026
First Seen
Valid until: 1/10/2027
Sources
Related Entities
Related Claims
UnverifiedUsing Jensen-Shannon divergence between time-domain and frequency-domain models as an uncertainty measure, AURC was 0.29 on the standard split (better than 0.36) and 0.54 under single-condition reproduction (better than 0.73).62% similarUnverifiedThe official core metrics for Decision Models are: an average of 90 milliseconds per decision, approximately 76% accuracy on public benchmarks, and free local execution.62% similarUnverifiedADE's scoring flow is option_scoring → softmax → argmax → margin, where margin is the difference between the top-2 scores and represents confidence.62% similarUnverifiedThat experiment reached the adaptation criterion specified in the paper (three consecutive sessions passing) at session 14, with both the bold rate and list rate metrics showing a downward trend across the first 36 sessions.62% similarUnverifiedWhen the sample size is small (e.g., only 5–10 successful requests), quantile estimation errors can be large; numpy.percentile or a larger sample size can be used to improve reliability.61% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1008214API
curl https://kongchang.com/api/v1/knowledge/claims/1008214MCP
get_claim(id=1008214)