{"total":19,"rows":[{"id":"2504.00147","title":"Universal Zero-shot Embedding Inversion","created":"2025-03-31","cited_by_count":8,"area":null},{"id":"2511.06571","title":"Rep2Text: Decoding Full Text from a Single LLM Token Representation","created":"2025-11-09","cited_by_count":7,"area":null},{"id":"2502.11308","title":"ALGEN: Few-shot Inversion Attacks on Textual Embeddings using Alignment and Generation","created":"2025-02-16","cited_by_count":4,"area":null},{"id":"2507.20783","title":"On The Role of Pretrained Language Models in General-Purpose Text Embeddings: A Survey","created":"2025-07-28","cited_by_count":3,"area":null},{"id":"2504.06669","title":"NLP Security and Ethics, in the Wild","created":"2025-04-09","cited_by_count":2,"area":null},{"id":"2510.13406","title":"When Embedding Models Meet: Procrustes Bounds and Applications","created":"2025-10-15","cited_by_count":2,"area":null},{"id":"2602.07090","title":"Concept-Aware Privacy Mechanisms for Defending Embedding Inversion Attacks","created":"2026-02-06","cited_by_count":2,"area":null},{"id":"2505.10354","title":"LDIR: Low-Dimensional Dense and Interpretable Text Embeddings with Relative Representations","created":"2025-05-15","cited_by_count":1,"area":null},{"id":"2505.16008","title":"LAGO: Few-shot Crosslingual Embedding Inversion Attacks via Language Similarity-Aware Graph Optimization","created":"2025-05-21","cited_by_count":1,"area":null},{"id":"2509.02411","title":"A Survey: Towards Privacy and Security in Mobile Large Language Models","created":"2025-09-02","cited_by_count":1,"area":null},{"id":"2510.11599","title":"SemCSE-Multi: Multifaceted and Decodable Embeddings for Aspect-Specific and Interpretable Scientific Domain Mapping","created":"2025-10-13","cited_by_count":1,"area":null},{"id":"2512.08809","title":"PrivTune: Efficient and Privacy-Preserving Fine-Tuning of Large Language Models via Device-Cloud Collaboration","created":"2025-12-09","cited_by_count":1,"area":null},{"id":"2606.26373","title":"Hybrid privacy-aware semantic search: SVD-truncated document geometry and CKKS-encrypted query reranking under a restricted threat model","created":"2026-06-24","cited_by_count":1,"area":null},{"id":"2505.05155","title":"FedTDP: A Privacy-Preserving and Unified Framework for Trajectory Data Preparation via Federated Learning","created":"2025-05-08","cited_by_count":0,"area":null},{"id":"2605.26433","title":"Vectors Are Not Neutral: Sensitive-Information Inference from Exported LLM Representations in Summarization","created":"2026-05-26","cited_by_count":0,"area":null},{"id":"2606.16461","title":"Privacy from Symmetry: Orthogonally Equivariant Transformers for LLM Inference","created":"2026-06-15","cited_by_count":0,"area":null},{"id":"2606.27976","title":"SHARD: cell-keyed residual splitting for alignment-resistant private dense retrieval","created":"2026-06-26","cited_by_count":0,"area":null},{"id":"2607.01276","title":"Embedding Inference Attack","created":"2026-07-01","cited_by_count":0,"area":null},{"id":"2608.18610","title":"Denoising-Aware Inversion: Revealing Privacy Risks in Noise-Protected Text Embeddings","created":"2026-08-19","cited_by_count":0,"area":null}],"next_cursor":null}