待验证90% 置信事实精确时间
Overfitting occurs when a model merely memorizes training data without being able to handle new data, while underfitting occurs when the model is too simple to capture patterns even in the training data.
1
来源数
90%
置信度
长期有效
时效性
2026/8/2
首次发现
来源
涉及实体
相关事实
待验证数据泄漏分为目标泄漏和训练-测试污染两类，会导致模型性能被系统性高估77% 相似已验证过拟合是指模型在训练数据上表现优异，但在未见过的测试数据上性能大幅下降的现象74% 相似待验证Benchmark overfitting is a systemic limitation where models score high through targeted training on test sets without corresponding improvements in generalization.73% 相似待验证过度对齐或过度拒绝（Over-refusal）是当前主流大语言模型普遍面临的工程难题，即模型被训练得过于保守导致对合理请求的误判率偏高70% 相似待验证训练数据中的重复内容会导致模型记忆化和性能下降70% 相似
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