Unverified50% confidenceFactExact time
The cost of a supervised small model is that it requires a certain amount of high-quality annotation, and its generalization ability is limited by the training distribution.
1
Sources
50%
Confidence
Long-term
Relevance
10/18/2026
First Seen
Sources
Related Entities
Related Claims
VerifiedFine-tuning typically requires only one percent or less of the original training cost to achieve domain performance close to that of a dedicated model.79% similarUnverifiedIn the early stages of training, models often need to process large numbers of samples that contribute little to final performance, constituting significant resource waste.78% similarUnverifiedOnly when a certain type of task is sufficiently high-frequency, stable, and cost-sensitive does migrating it from a general-purpose model to a specially trained model potentially realize significant cost benefits.78% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1059557API
curl https://kongchang.com/api/v1/knowledge/claims/1059557MCP
get_claim(id=1059557)