Unverified50% confidenceFactExact time
In adversarial training, there is no uniform convergence rate.
1
Sources
50%
Confidence
Long-term
Relevance
11/6/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedSingle-pass training brings only modest overall calibration improvement and no improvement whatsoever in the early prefix stage.76% similarUnverifiedThe model did not use any pretrained weights during training.72% similarUnverifiedThe approach with fine-tuning but without tool harness optimization, despite a larger training volume, achieved far less than AdaRSI.71% similarUnverifiedSMD's repulsion mechanism does not require the discriminator commonly used in adversarial training, nor does it require online score estimation; it is merely an additional constraint on the training objective, and the training overhead is almost zero.69% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1142248API
curl https://kongchang.com/api/v1/knowledge/claims/1142248MCP
get_claim(id=1142248)