Unverified50% confidenceFactExact time
Counterfactual results refer to estimates obtained from model simulation rather than actual observation; the loss-reduction figures in this paper are counterfactual results rather than field-trial observations.
1
Sources
50%
Confidence
Long-term
Relevance
10/28/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedNegative Prompts can explicitly tell the model which elements are not desired, so as to avoid results skewing toward a realistic style.69% similarUnverifiedWhen analyzing the removed samples, the researchers identified previously understudied sources of safety degradation such as tool-execution failures and narrative arithmetic, and the gradient signal shows that these patterns are associated with unsafe behavior.69% similarUnverifiedData from failure cases has unique value in telling models which paths do not work, and this type of negative information is severely lacking in public literature.69% similarUnverifiedIn data quality validation, the costs of different errors are asymmetric: incorrectly accepting dirty data may cause downstream analysis to break down, while falsely rejecting good data only loses one sample.66% similarUnverifiedInference methods based on model internal features face a trade-off between false positives and false negatives66% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1106210API
curl https://kongchang.com/api/v1/knowledge/claims/1106210MCP
get_claim(id=1106210)