Unverified50% confidenceFactExact time
An explicit confidence target means the user specifies a target value p in the prompt, and the model accordingly directly chooses whether to answer or abstain, with the goal that the accuracy on answered questions reaches at least p.
1
Sources
50%
Confidence
Long-term
Relevance
10/27/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedA well-calibrated model is one where the actual accuracy of predictions with output probability P is also close to P across all such predictions; calibration quality is commonly measured using the ECE (Expected Calibration Error) metric.67% similarPartially Verified/goal功能利用LLM自身的判断能力来决定任务是否完成，而非依赖复杂的外部控制逻辑67% similarUnverifiedUsing a confidence-first strategy during decoding (prioritizing the positions the model is most confident about) typically delivers significantly better generation quality than uniformly revealing a fixed proportion of tokens, because it allows the model to decide on difficult positions after having more context.66% similarUnverifiedThe correct approach to deploying large models is to first clarify the target precision and target context length, then work backwards to determine the required memory, rather than simply looking at parameter count.66% similarUnverifiedAfter the model in Goal mode receives the prompt, it only estimates what to do in the first round; after completing and verifying that round, it then checks whether the task is finished, and the total number of rounds is unknown in advance.66% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1102075API
curl https://kongchang.com/api/v1/knowledge/claims/1102075MCP
get_claim(id=1102075)