Expired60% confidenceSolutionExact time
Large models can be used to automatically generate synthetic training data based on domain documents to construct question-answer pairs, and typically thousands to tens of thousands of training pairs are needed to achieve significant results.
2
Sources
60%
Confidence
Medium-term (~90 days)
Relevance
7/12/2026
First Seen
Valid until: 10/10/2026(expired)
Sources
Related Claims
Unverified后训练阶段使用几万对到几十万对'用户请求+标准回答'的配对数据来训练模型理解人类指令意图82% similarUnverified对于图像到矢量这类复杂生成任务,通常需要数千到数万对高质量样本才能训练出效果稳定的模型78% similarUnverifiedTraditional large model training relies heavily on manually annotated data and external corpus collection, which are typically the bottlenecks constraining iteration speed.77% similarUnverifiedThe energy consumption during the training phase of large models is approximately hundreds of times that of the inference phase.74% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/489919API
curl https://kongchang.com/api/v1/knowledge/claims/489919MCP
get_claim(id=489919)