Unverified50% confidenceOpinionExact time
Reconstructing individual events may cause MLM to overemphasize noisy or low-information observations and waste its capacity on low-value signals.
1
Sources
50%
Confidence
Long-term
Relevance
10/22/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedHigh bias means the model is too simple and leads to underfitting, while high variance means the model has learned noise and leads to overfitting, and the two tend to trade off against each other.75% similarVerifiedThere is a fundamental trade-off between low-cost data collection and data quality; cheap but excessively noisy data may actually harm final model performance.75% similarUnverified膨胀、过时、充满噪声的评估集比没有评估集更糟糕，因为它会给出误导性的信号74% similarVerifiedNoise information in the context degrades model reasoning accuracy in a nonlinear manner73% similarUnverified过度膨胀的上下文会稀释模型注意力、抬高推理成本，甚至引入噪声导致幻觉73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1084405API
curl https://kongchang.com/api/v1/knowledge/claims/1084405MCP
get_claim(id=1084405)