Unverified50% confidenceFactExact time
Context accuracy is a metric in the RoboSpatial-Home benchmark that measures the quality of spatial context prediction, typically requiring the IoU between the predicted region and the ground-truth placeable region to exceed a threshold.
1
Sources
50%
Confidence
Long-term
Relevance
10/19/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedExperiments show that the gated objective achieved the highest average accuracy on both datasets, verifying that objective reliability and evaluation priority can be optimized independently67% similarUnverifiedA robust embodied AI evaluation benchmark should consider sample efficiency and generalization across randomized scenarios, not just task completion rate and spatial accuracy.66% similarVerifiedThe area under the PR curve is called AP (Average Precision), and mAP (mean Average Precision) is the standard evaluation metric for object detection models.65% similarVerifiedCalibration is typically visualized using a reliability diagram (calibration curve), with confidence on the horizontal axis and the actual accuracy of samples in that interval on the vertical axis.65% similarUnverifiedThe effectiveness of object detection model improvements needs to be validated by comparing core metrics such as accuracy (mAP) and inference speed (FPS).65% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1068940API
curl https://kongchang.com/api/v1/knowledge/claims/1068940MCP
get_claim(id=1068940)