Unverified50% confidencePredictionExact time
Different training objectives (such as contrastive learning and masked language modeling) may produce different α ranges, offering a new dimension for comparing different training paradigms.
1
Sources
50%
Confidence
Long-term
Relevance
10/14/2026
First Seen
Sources
Related Entities
Related Claims
Unverified不同模型系列的工具调用输出格式差异根源于指令微调阶段使用的训练数据差异74% similarUnverified不同模型在抗诱导能力上的差异很大程度上源于后训练阶段（post-training）的策略差异74% similarUnverifiedThe differences in how models respond to prompts mainly come from three levels: training data composition, architecture and context window, and coverage of the continued-training corpus.74% similarUnverifiedWhich factors in the training process drive the rise of α, and how different training objectives, data distributions, and model architectures affect this slope, remain to be answered.73% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1023602API
curl https://kongchang.com/api/v1/knowledge/claims/1023602MCP
get_claim(id=1023602)