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Privacy

2794 directly classified papers

Papers per year

Papers

FiMMIA: scaling semantic perturbation-based membership inference across modalities EACL 2026

Continual Pretraining on Encrypted Synthetic Data for Privacy-Preserving LLMs EACL 2026

Personal Information Parroting in Language Models EACL 2026

LitE-SQL: A Lightweight and Efficient Text-to-SQL Framework with Vector-based Schema Linking and Execution-Guided Self-Correction EACL 2026

Marking Code Without Breaking It: Code Watermarking for Detecting LLM-Generated Code EACL 2026

PATCH: Mitigating PII Leakage in Language Models with Privacy-Aware Targeted Circuit PatcHing EACL 2026

DuFFin: A Dual-Level Fingerprinting Framework for LLMs IP Protection EACL 2026

Image Corruption-Inspired Membership Inference Attacks against Large Vision-Language Models EACL 2026

Synthetic Doctor-Patient Dialogue Generation for Robust Medical ASR: A Scalable Pipeline for Vocabulary Expansion and Privacy Preservation EACL 2026

RFNNS: Robust Fixed Neural Network Steganography with Universal Text-to-Image Models AAAI 2026

ROVER: Robust Generative Continual Identity Unlearning Against Relearning Attacks AAAI 2026

Dual-View Inference Attack: Machine Unlearning Amplifies Privacy Exposure AAAI 2026

PeriUn: Enhancing Unlearning by Selectively Forgetting Peripheral Samples AAAI 2026

Privacy Auditing of Multi-Domain Graph Pre-Trained Model Under Membership Inference Attacks AAAI 2026

Plug-and-Play Parameter-Efficient Tuning of Embeddings for Federated Recommendation AAAI 2026

TabGeoFlow: A Geometric Flow Matching Model for Tabular Data Synthesis AAAI 2026

Robust Watermarking on Gradient Boosting Decision Trees AAAI 2026

Forget What Has Seen: Selective Concept Unlearning in Segmentation Foundation Models AAAI 2026

Rethinking Membership Inference Attacks for CLIP AAAI 2026

OPTION: An Online Pricing Strategy for Asynchronous Federated Learning Against Free-Riding Attacks AAAI 2026

On the Misalignment Between Data Learnability and Forgettability in Machine Unlearning AAAI 2026

Retaliatory Attacks Against Federated Unlearning via Data Leakage AAAI 2026

Injection, Attack and Erasure: Revocable Backdoor Attacks via Machine Unlearning AAAI 2026

FedShard: Federated Unlearning with Efficiency Fairness and Performance Fairness AAAI 2026

Privacy-Preserving Argumentative Explanations (Student Abstract) AAAI 2026