Key papers

• Embedding Inference Attack (2026)
  Cedric Fitiavana Raelijohn et al.
  5.01
• Willing but Unable: Separating Refusal from Capability in Code LLMs via Abliteration (2026)
  Cristina Carleo et al.
  4.95
• AttackPathGNN: Cross-function vulnerability detection in smart contracts using state interference graphs and conjunction pooling (2026)
  Gabriela Dobrita et al.
  4.95
• FlowGuard: Flow Matching for Identity-Independent Detection of Data-Free Model Stealing Attacks on Energy System Intrusion Detection Systems (2026)
  Maxime Schwarzer et al.
  4.33
• Testing LLM Arithmetic Reasoning Generalization with Automatic Numeric-Remapping Attacks (2026)
  Malia Barker et al.
  4.33
• Ghost: Plausible Yet Unlearnable Trajectories via On-Manifold Substitution for Next-POI Privacy (2026)
  Zhenyu Yu et al.
  4.33
• Beyond Her: Safety Dynamics in Role-play AI Companions (2026)
  Zehang Deng (Minhui) et al.
  4.33
• Sign in the Air to Unlock: An Interface for authentication in Virtual and Augmented Reality Powered by Point-Voxel Cross-Attention Network (2026)
  Neda Abdolrahimi et al.
  3.51
• Towards an Automated Test of LLM Security Knowledge (2026)
  Shufan Chai et al.
  3.51
• Faster-GCG: Efficient Discrete Optimization Jailbreak Attacks against Aligned Large Language Models (2026)
  Xiao Li et al.
  1.94
• Context-Aware Detection and Victim-Centered Response Generation for Online Harassment in Private Messaging (2026)
  Pinxian Lu et al.
  1.94
• Lossless Anti-Distillation Sampling (2026)
  Zibo Diao et al.
  1.94
• Privacy-preserving Targeted Advertising (2017)
  Theja Tulabandhula et al.
  —
• Successive Point-of-Interest Recommendation with Local Differential Privacy (2019)
  Jong Seon Kim et al.
  —
• Practical Privacy Preserving POI Recommendation (2020)
  Chaochao Chen et al.
  —
• Trustworthy Recommender Systems (2022)
  Shoujin Wang et al.
  —
• A Comprehensive Survey on Trustworthy Recommender Systems (2022)
  Wenqi Fan et al.
  —
• Untargeted Attack against Federated Recommendation Systems via Poisonous Item Embeddings and the Defense (2022)
  Yang Yu et al.
  —
• Evaluating the Robustness of Conversational Recommender Systems by Adversarial Examples (2023)
  Ali Montazeralghaem and James Allan
  —
• Towards Differential Privacy in Sequential Recommendation: A Noisy Graph Neural Network Approach (2023)
  Wentao Hu et al.
  —
• Private Matrix Factorization with Public Item Features (2023)
  Mihaela Curmei et al.
  —
• Beyond Random Noise: Insights on Anonymization Strategies from a Latent Bandit Study (2023)
  Alexander Galozy et al.
  —
• Multi-Resolution Diffusion for Privacy-Sensitive Recommender Systems (2023)
  Derek Lilienthal et al.
  —
• Poisoning Attacks against Recommender Systems: A Survey (2024)
  Zongwei Wang et al.
  —
• Robust Explainable Recommendation (2024)
  Sairamvinay Vijayaraghavan et al.
  —
• Privacy-preserving recommender system using the data collaboration analysis for distributed datasets (2024)
  Tomoya Yanagi et al.
  —
• Adversarial Text Rewriting for Text-aware Recommender Systems (2024)
  Sejoon Oh et al.
  —