Unverified50% confidenceOpinionExact time
Achieving a significant improvement in programming capabilities through post-training on the same base model provides a new model iteration approach for teams with limited computing resources.
1
Sources
50%
Confidence
Long-term
Relevance
9/11/2026
First Seen
Sources
Related Entities
Related Claims
Unverified在推理阶段投入更多工程智慧可以带来实质性的性能跃升,而不只是训练更大模型79% similarUnverifiedInvesting more computation at the inference stage (test-time compute scaling) can significantly improve model performance, and is often more cost-effective than an equivalent investment of computation at the training stage.78% similarUnverifiedThe Ziyue large model made extensive use of educational corpora such as textbooks, exercises, and problem-solving processes during the pre-training and fine-tuning stages, giving it stronger professionalism on educational tasks.76% similarUnverified训练秘诀(Training Recipe)包括数据配比策略、学习率调度曲线、过滤规则、对齐技术等,往往比模型架构本身更难被复现76% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/900633API
curl https://kongchang.com/api/v1/knowledge/claims/900633MCP
get_claim(id=900633)