Unverified50% confidenceOpinionExact time
This method relies on a frozen code language model and two adapters, with higher training and inference costs than simple classifiers.
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Relevance
10/21/2026
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Related Claims
Unverified大语言模型的训练目标是最大化下一个Token的预测概率而非最大化代码安全性，这两个目标在数学上不等价78% similarUnverifiedUneven distribution of training corpus is the root cause of deviations in model capability, and a large model's code generation ability for a language depends heavily on the volume, diversity and quality of that language's code in the pre-training data.76% similarVerifiedThe underlying mechanism by which large language models generate code is conditional probability prediction based on massive training corpora, and the model does not truly understand code logic75% similarUnverifiedThe combination of frozen features plus a lightweight reasoning head preserves the generalization ability of the pretrained model and avoids the cost of large-scale fine-tuning.74% similar
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