Unverified50% confidenceSolutionExact time
Decision quality is highly dependent on the accuracy of the posterior probability P(y|x); model overconfidence leads to systematic bias in expected loss calculations, so it is recommended to first perform probability calibration such as Platt scaling or isotonic regression.
1
Sources
50%
Confidence
Long-term
Relevance
9/11/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedThe overconfidence of a model answering directly while skipping retrieval is technically referred to as miscalibration, meaning there is a systematic deviation between confidence and actual accuracy.72% similarUnverified精确数值计算需要严格遵循确定性规则,这与基于统计概率的token预测机制存在根本性矛盾71% similarUnverifiedIn machine learning evaluation, precision and recall often have a trade-off relationship, and increasing recall typically leads to more genuine products being misclassified.70% similarUnverifiedThe more independent requirements included in a single prompt, the more the probability of the model omitting or incorrectly implementing certain requirements grows non-linearly; the MVP strategy improves reliability by narrowing the model's decision space.70% similarUnverified对MoE模型的量化需要格外谨慎,因稀疏激活使专家参数数值分布集中,低比特量化易造成路由偏差导致能力退化70% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/899645API
curl https://kongchang.com/api/v1/knowledge/claims/899645MCP
get_claim(id=899645)