Unverified50% confidenceFactExact time
The evaluated VLM itself remains completely frozen, and all optimization occurs at the level of the reasoning program and surrounding code, requiring no gradient updates, additional training data, or modification of model weights.
1
Sources
50%
Confidence
Long-term
Relevance
10/27/2026
First Seen
Sources
Related Entities
Related Claims
UnverifiedA frozen model refers to a model whose weight parameters all remain unchanged during the inference phase, with no fine-tuning, adapter training, or online learning performed.74% similarUnverified使用VLM提示可直接分割岩点,无需从零创建数据集训练专门模型,代表从训练专用模型转向提示通用模型的开发范式转变72% similarUnverified当前的LLM一旦完成训练其参数即被冻结,只能通过微调或RAG等外部机制来更新68% similarUnverifiedThe ABACUS framework improves multi-step reasoning by composing reusable programs to freeze the judgment model's decisions, and the model parameters are not updated throughout.68% similarUnverifiedVLM训练需要精确对齐的图文配对数据集,若图文对应关系出现偏差,模型会学到错误的跨模态映射68% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1102165API
curl https://kongchang.com/api/v1/knowledge/claims/1102165MCP
get_claim(id=1102165)