Unverified50% confidenceOpinionExact time
"Get the pipeline working with a strong model first, then train a small model" is an extension of the knowledge distillation idea to the Agent scenario; if the order is reversed (train the model first, then change the pipeline), it often means all the data is invalidated and retraining is required.
1
Sources
50%
Confidence
Long-term
Relevance
11/6/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedAI编程工具自研模型常采用大模型生成训练数据加小模型专项微调的策略,Replit的replit-code、Tabnine的本地小模型遵循类似逻辑75% similarUnverifiedSensitive information from training data can be extracted by reverse-engineering model weights, which is known as a model inversion attack.75% similarVerifiedFine-tuning involves taking an existing large model and further training it with a specially prepared proprietary dataset, thereby changing the model's weight values75% similarUnverifiedKnowledge distillation guides the training of a smaller model using soft labels from a larger model, whereas pruning directly inherits knowledge from the weights of the larger model.74% similarUnverifiedA model's actual behavior is jointly determined by training weights, system prompts, and runtime context; looking at the prompt alone cannot fully reproduce the complete picture of the product.74% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1142467API
curl https://kongchang.com/api/v1/knowledge/claims/1142467MCP
get_claim(id=1142467)