Unverified50% confidenceOpinionExact time
The cross-modal discrepancy-driven sample mining method is more robust than traditional uncertainty sampling based on single-model confidence, because it uses complementary information from the physical world as the basis for judgment.
1
Sources
50%
Confidence
Long-term
Relevance
8/9/2026
First Seen
Sources
自建多模态数据集:从500帧到300万帧的自动化标注实践
Related Claims
Unverified设计判断力这类偏主观的能力很难通过统一基准测试量化71% similarUnverified集成方法有效的原因在于不同模型的错误往往具有不相关性,综合多个模型判断可抵消个体偏差69% similarUnverified将概念推理量化为单一指数可能丢失多维度、情境依赖的推理能力信息,误导下游应用选型决策69% similarUnverifiedThe field of robotic world models has long lacked unified, easy-to-use evaluation tools, and researchers using different metrics and datasets to validate their own results make cross-study comparison difficult.68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/712773API
curl https://kongchang.com/api/v1/knowledge/claims/712773MCP
get_claim(id=712773)