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626 directly classified papers

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Papers

Text Embedding Inversion Security for Multilingual Language Models ACL 2024
Assessing Authenticity and Anonymity of Synthetic User-generated Content in the Medical Domain EACL 2024
Transferable Embedding Inversion Attack: Uncovering Privacy Risks in Text Embeddings without Model Queries ACL 2024
Machine Unlearning of Pre-trained Large Language Models ACL 2024
VoiceDefense: Protecting Automatic Speaker Verification Models Against Black-box Adversarial Attacks INTERSPEECH 2024
Data Anonymization for Privacy-Preserving Large Language Model Fine-Tuning on Call Transcripts EACL 2024
Towards More Realistic Membership Inference Attacks on Large Diffusion Models WACV 2024
Neural Codec-based Adversarial Sample Detection for Speaker Verification INTERSPEECH 2024
Detecting Personal Identifiable Information in Swedish Learner Essays EACL 2024
Defending Against Backdoor Attacks by Layer-wise Feature Analysis (Extended Abstract) IJCAI 2024
Mixing Gradients in Neural Networks as a Strategy To Enhance Privacy in Federated Learning WACV 2024
An Inversion Attack Against Obfuscated Embedding Matrix in Language Model Inference EMNLP 2024
Can Watermarks Survive Translation? On the Cross-lingual Consistency of Text Watermark for Large Language Models ACL 2024
Scalable Federated Unlearning via Isolated and Coded Sharding IJCAI 2024
Protecting Object Detection Models from Model Extraction Attack via Feature Space Coverage IJCAI 2024
Membership Inference Attack Using Self Influence Functions WACV 2024
Probabilistically Robust Watermarking of Neural Networks IJCAI 2024
Machine Unlearning: Challenges in Data Quality and Access IJCAI 2024
Spoof Diarization: "What Spoofed When" in Partially Spoofed Audio INTERSPEECH 2024
Handling Name Errors of a BERT-Based De-Identification System: Insights from Stratified Sampling and Markov-based Pseudonymization EACL 2024
Deidentifying a Norwegian Clinical Corpus - an Effort to Create a Privacy-preserving Norwegian Large Clinical Language Model EACL 2024
On provable privacy vulnerabilities of graph representations NIPS 2024
High-Fidelity Gradient Inversion in Distributed Learning AAAI 2024
Trap-MID: Trapdoor-based Defense against Model Inversion Attacks NIPS 2024
Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models NIPS 2024