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HydraPrompt: An Adaptive and Asymmetric Framework of Vision-Language Models for Synthetic Image Detection Geometry-Aware Representation Denoising for Robust Multi-view 3D Reconstruction 3D Gaussian Map with Open-Set Semantic Grouping for Vision-Language Navigation On the Push-Based Asynchronous Federated Learning: A Bias-Correction Aggregation Approach OmniInteract: Benchmarking Real-World Streaming Interaction for Real-Time Omnimodal Assistants CNNs, Transformers, Hybrid, and Vision Language Models for Skin Cancer Detection VesselSim: learning 3D blood vessel segmentation without expert annotations Erased but Exploitable: Black-box Embedding-Aware Prompting Against Unlearned Text-to-Image Diffusion Models VisualNeedle: Benchmarking Active Visual Search in Information-Dense Scenes DuoGesture: Neuro-Inspired and Biomechanically Informed Dual-Stream Co-Speech Gesture Generation RadarSim: Simulating Single-Chip Radar via Multimodal Neural Fields RoMo: A Large-Scale, Richly Organized Dataset and Semantic Taxonomy for Human Motion Generation The Rescue Effect: Spatio-Semantic Early Exit Bypasses Quantization Collapse in CLIP When Rule Violations Are Rare: Chimera Training for Logical Anomaly Detection Detail Consistent Stage-Wise Distillation for Efficient 3D MRI Segmentation Sparse-LiDAR Prompting of Monocular Geometry Foundations: An Empirical Study Toward Long-Range Driving Depth AirCast-SR: A Foundation Model for Kilometer-Scale Atmospheric Super-Resolution via Latent Consistency Diffusion Personalized Generative Models for Contextual Debiasing Cross-scale Aligned Supervision for Training GANs Joint Instance Segmentation and Geometric Attribute Regression for Roof Structures in Aerial Imagery Dimensional Distribution Emotion State: Leveraging Valence and Arousal as a Common Embedding Space for Visual Emotion Analysis TSFMAudit: Data Contamination Auditing in Forecasting Time Series Foundation Models Clinically-Grounded Counterfactual Reasoning for Medical Video Diagnosis Triadic Dynamics Aware Diffusion Posterior Sampling for Inverse Problems: Optimizing Guidance and Stochasticity Schedules Comparative Study of Vision-Based Metric Measurement for Large-Scale Planar Scenes LongAV-Compass: Towards Unified Evaluation of Minute-Scale Audio-Visual Generation Across T2AV, I2AV, and V2AV The Constraint Tax: Measuring Validity-Correctness Tradeoffs in Structured Outputs for Small Language Models SilIF: Silhouette-Augmented Isolation Forest for Unsupervised Transaction Fraud Detection Multi-Modal Building Inspection via Perceiver IO Fusion of Satellite and Street-Level Imagery E$^3$C: Video Generation with 3D Environmental Memory and Ego-Exo Human Pose Control Share More, Search Less: Collaborative Parallel Thinking for Efficient Test-Time Scaling Unveiling the Fragility of Vision-Language Models: Multi-Modal Adversarial Synergy via Texture-Constrained Perturbations and Cross-Modal Optimization Sleep-stage efficient classification using a lightweight self-supervised model Underwater360: Reconstructing Underwater Scenes from Panoramic Images with Omnidirectional Gaussian Splatting Rethinking Weakly-supervised Video Temporal Grounding From a Game Perspective Sentinel: Embodied Cooperative Spatial Reasoning and Planning LongCat-Video-Avatar 1.5 Technical Report GEM: Geometric Entropy Mixing for Optimal LLM Data Curation Uncertainty-Aware Gaussian Map for Vision-Language Navigation Frequency-Guided Fusion For RGB-Thermal Semantic Segmentation BioFact-MoE: Biologically Factorized Mixture of Experts for Vision-Language Prognostic Modeling in Hepatocellular Carcinoma A multifractal-based masked auto-encoder: an application to medical images Benchmarking Convolutional, Transformer, Hybrid, and Vision Language Models for Multi Disease Retinal Screening Unified Panoramic Geometry Estimation via Multi-View Foundation Models Not All Modalities Are Equal: Instruction-Aware Gating for Multimodal Videos OmniGF: A Dual-Branch Vision-Language Framework for Unified Gaze Following Zero-Shot Object Re-Identification in Egocentric Kitchen Videos via Multi-Stage SAM3 Feature Fusion Evi-Steer: Learning to Steer Biomedical Vision-Language Models through Efficient and Generalizable Evidential Tuning Planning Neural Dynamics with Lie Group Embedding through Supervised Projective Manifold Learning AnchorDiff: Training-Free Concept Grounding for MM-DiTs via Anchor-Based Graph Propagation
Cordon-MAS: 정보 흐름 제어를 통해 Knowledge Poisoning으로부터 RAG 방어
Zhe Yu, Wenp · 2026-05-27 · via cs updates on arXiv.org

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요약:리트리뷰얼-액세스먼트드 재네레이션(RAG)은 점점 높은 위험성 있는 응용 프로그램의 핵심을 이루고 있지만, Confundo 스타일의 독성 공격에 취약하게 남아있다. 이는 적대적으로 최적화된 문서가 생성된 출력을 조작하는 경우이다. 기존 방어책은 독성 증거를 탐지하는 것으로 해를 막을 수 있다고 가정한다. 우리는 이 가정이 잘못되었음을 보여준다: 모델은 검색된 증거에서 모순을 탐지할 수 있지만, 여전히 독성 주장에 따라 행동할 수 있다. 우리는 코르돔 원리를 소개한다 -- 최종 합성이 가능한 에이전트는 신뢰할 수 없는 자연어 증거에 접근하지 못한다 -- 그리고 이를 CORDON-MAS, 분할된 프레임워크를 통해 구현한다. 이 프레임워크는 증거 추출, 다양한 출처 검토, 답변 합성을 비대칭 메모리 권한을 가진 에이전트로 분리하여 이 원리를 아키텍처적으로 강제한다. 다섯 개의 BEIR 데이터셋에서 CORDON-MAS는 방어되지 않은 RAG에 비해 공격 성공률을 92.4% 감소시킨다. 이는 RAG 독성을 탐지 문제에서 정보 흐름 제어 문제로 재정의한다.
주제: 암호학 및 보안 (cs.CR); 인공지능 (cs.AI)
참조: arXiv:2605.26754 [cs.CR]
  (또는 arXiv:2605.26754v1 [cs.CR] 이 버전용)
  https://doi.org/10.48550/arXiv.2605.26754

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From: Meng Han [이메일 보기]
[v1] 화, 26 월 2026 09:27:19 UTC (1,102 KB)