Unverified50% confidenceBenchmarkExact time
On the tokenizer membership inference benchmark, RTAM-Fusion outperforms the Vocabulary Overlap baseline on both AUC and balanced accuracy while requiring fewer shadow tokenizers.
1
Sources
50%
Confidence
Medium-term (~90 days)
Relevance
10/30/2026
First Seen
Valid until: 1/28/2027
Sources
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Unverified混合架构中，仅当规则匹配失败或置信度低于阈值时才调用大模型兜底，通常可减少60%-80%的API调用量60% similarUnverifiedA compact fusion model using the same five evidence streams and frozen encoders achieved only 0.7652 AUROC under matched inputs, while PRISM reached 0.9092 under the same settings.60% similarUnverifiedIn annotation quality control, an IoU ≥ 0.5 is usually regarded as an acceptable match, and samples below that threshold are treated as disagreement samples.60% similarUnverifiedIn cross-model validation, REVA's accuracy is at least on par with VulTriage on three open-source LLMs, and about 10% higher on two of them.60% similarUnverifiedAt the full VTF900 gallery scale (N=900) under frontal conditions, the ViT-B model achieves 97.68% AUC and 51.10% TAR@1%FAR.59% similar
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