Unverified50% confidenceFactExact time
Each of Jeff's answers comes with a confidence score; on chain questions, when the question depth exceeds what can be grasped at a glance, confidence drops along with accuracy.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/4/2026
First Seen
Valid until: 1/2/2027
Sources
Related Entities
Related Claims
UnverifiedTraditional confidence calibration methods mostly rely on model-generated output text or sequence-based probability statistics, making it difficult to capture complex failure patterns in multi-turn agent interactions.71% similarUnverifiedThe more vague the question, the more the model tends to output statistically common, mediocre answers; the more precise the constraints, the closer the output is to the specific requirement.68% similarUnverified分层漏斗每一层输出置信度分数，当置信度低于预设阈值时请求才下沉到下一层；阈值过高导致请求不必要流向下层，阈值过低引发误识别68% similarUnverifiedtop-1%贪婪解码准确率只考察单token预测的一致性，无法捕捉量化对长序列生成质量的真实影响，微小偏差会在自回归生成中累积68% similarUnverifiedThe 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.68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/973502API
curl https://kongchang.com/api/v1/knowledge/claims/973502MCP
get_claim(id=973502)