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Updated: Feb 13, 2026

Usability Evaluation of Augmented Reality: A Neuro-Information-Systems Study
05:43

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Published on: November 30, 2022

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セキュアな検索拡張生成システムにおけるセマンティックキャッシングの敵対的耐性の強化

Mohanad Afiffy1, Mohamed Waleed Fakhr2, Fahima A Maghraby3

  • 1College of Engineering and Technology, Arab Academy for Science and Technology, Cairo, Egypt. m.abdelba33713@student.aast.edu.

Scientific reports
|February 11, 2026
PubMed
まとめ

新しいSAFE-CACHEシステムは、セマンティックキャッシングに対する敵対的攻撃を防ぐことにより、大規模言語モデル（LLM）のセキュリティを強化します。自然言語処理アプリケーションにおける信頼性と計算コストを大幅に改善します。

キーワード:
セマンティックキャッシング検索拡張生成大規模言語モデル敵対的攻撃セキュリティ自然言語処理

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