Unverified50% confidenceBenchmarkExact time
The Expected Calibration Error (ECE) increased in seven out of eight event pairs, and in affected scenarios, 12%–51% of the area was confidently mislabeled by the model with near-zero accuracy.
1
Sources
50%
Confidence
Long-term
Relevance
10/8/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedExpected Calibration Error (ECE) bins prediction samples by confidence level, computes the weighted average of the difference between predicted confidence and actual accuracy within each bin, and ideally approaches 0.73% similarUnverified研究者通常使用期望校准误差(ECE)来量化模型的校准程度70% similarUnverifiedJCE所谓的'可靠'实际只有约60%的准确率,因误差累积连续5步后整体成功率仅剩约7.8%69% similarUnverified当综合评估指数中顶尖模型得分接近天花板时会出现基准饱和问题,60分对59分的差距在统计学上通常处于误差范围之内68% similarUnverifiedTop academic deepfake detectors can see their accuracy plummet from 99% to below 60% when faced with previously unseen generative models, a phenomenon known as the cross-model generalization problem.67% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/986743API
curl https://kongchang.com/api/v1/knowledge/claims/986743MCP
get_claim(id=986743)