Unverified50% confidenceFactExact time
模型权重本身在推理时是冻结的,无法将新信息永久写入
1
Sources
50%
Confidence
Long-term
Relevance
7/14/2026
First Seen
Sources
Adaptive Recall:基于MCP协议的AI助手持久记忆方案解析
Related Claims
UnverifiedPrompt engineering techniques such as chain-of-thought, few-shot prompting, and self-consistency cannot enable a model to access information beyond its training cutoff date, cannot guarantee the precision of floating-point arithmetic, and cannot handle external files the model has never seen.69% similarUnverifiedWhen the model itself lacks the capability to understand a specific problem, no amount of prompt engineering can compensate for this deficiency68% similarUnverified作者不再把KEEP决策当作模型改进的证明,在最近一次审计中模型在新数据上的对比结果是不确定的,模型被保留仅因没有足够强的理由回滚65% similarUnverifiedTraditional large models have a fundamental statelessness limitation: each inference is an independent forward-propagation process and cannot actively trigger any external operations.64% similarUnverifiedStatic benchmark scores cannot capture a model's actual capabilities in open-ended dialogue, reasoning, creative writing, and other complex tasks64% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/503334API
curl https://kongchang.com/api/v1/knowledge/claims/503334MCP
get_claim(id=503334)