Image de couverture de livre

Estimating Privacy Leakage of Augmented Contextual Knowledge in Language Models

Fuente: arXiv

Enregistré dans:

Détails bibliographiques
Auteurs principaux:	Flemings, James, Jiang, Bo, Zhang, Wanrong, Takhirov, Zafar, Annavaram, Murali
Format:	Preprint
Publié:	2024
Sujets:	Computation and Language Machine Learning
Accès en ligne:	Acceder al recurso
Tags:	Ajouter un tag Pas de tags, Soyez le premier à ajouter un tag!

Documents similaires

Differentially Private Knowledge Distillation via Synthetic Text Generation
par: Flemings, James, et autres
Publié: (2024)

Differentially Private Next-Token Prediction of Large Language Models
par: Flemings, James, et autres
Publié: (2024)

PrivacySIM: Evaluating LLM Simulation of User Privacy Behavior
par: Flemings, James, et autres
Publié: (2026)

Adaptively Private Next-Token Prediction of Large Language Models
par: Flemings, James, et autres
Publié: (2024)

Differentially Private Retrieval-Augmented Generation
par: Tang, Tingting, et autres
Publié: (2026)

DELTA: Dynamic Layer-Aware Token Attention for Efficient Long-Context Reasoning
par: Zarch, Hossein Entezari, et autres
Publié: (2025)

DEL: Context-Aware Dynamic Exit Layer for Efficient Self-Speculative Decoding
par: Zarch, Hossein Entezari, et autres
Publié: (2025)

Membership Inference Attacks and Privacy in Topic Modeling
par: Manzonelli, Nico, et autres
Publié: (2024)

Sanitize Your Responses: Mitigating Privacy Leakage in Large Language Models
par: Fu, Wenjie, et autres
Publié: (2025)

Differentially Private In-context Learning via Sampling Few-shot Mixed with Zero-shot Outputs
par: Flemings, James, et autres
Publié: (2025)

Automating Governing Knowledge Commons and Contextual Integrity (GKC-CI) Privacy Policy Annotations with Large Language Models
par: Chanenson, Jake, et autres
Publié: (2023)

Knowledge-Augmented Large Language Models for Personalized Contextual Query Suggestion
par: Baek, Jinheon, et autres
Publié: (2023)

Contextual Text Denoising with Masked Language Models
par: Sun, Yifu, et autres
Publié: (2019)

PrivacyMind: Large Language Models Can Be Contextual Privacy Protection Learners
par: Xiao, Yijia, et autres
Publié: (2023)

Embedding Attack Project (Work Report)
par: Pu, Jiameng, et autres
Publié: (2024)

Tracing Privacy Leakage of Language Models to Training Data via Adjusted Influence Functions
par: Liu, Jinxin, et autres
Publié: (2024)

What Does the Server See? Understanding Privacy Leakage from Large Language Models in Split Inference
par: Fan, Mingyuan, et autres
Publié: (2026)

Narrative Analysis of True Crime Podcasts With Knowledge Graph-Augmented Large Language Models
par: Leng, Xinyi, et autres
Publié: (2024)

Retrieval-Augmented and Knowledge-Grounded Language Models for Faithful Clinical Medicine
par: Liu, Fenglin, et autres
Publié: (2022)

EIA: Environmental Injection Attack on Generalist Web Agents for Privacy Leakage
par: Liao, Zeyi, et autres
Publié: (2024)

Sequence-Level Leakage Risk of Training Data in Large Language Models
par: Tiwari, Trishita, et autres
Publié: (2024)

Fast NF4 Dequantization Kernels for Large Language Model Inference
par: Qi, Xiangbo, et autres
Publié: (2026)

Benchmarking Benchmark Leakage in Large Language Models
par: Xu, Ruijie, et autres
Publié: (2024)

CATS: Contextually-Aware Thresholding for Sparsity in Large Language Models
par: Lee, Donghyun, et autres
Publié: (2024)

Large Language Models Are Latent Variable Models: Explaining and Finding Good Demonstrations for In-Context Learning
par: Wang, Xinyi, et autres
Publié: (2023)

A False Sense of Privacy: Evaluating Textual Data Sanitization Beyond Surface-level Privacy Leakage
par: Xin, Rui, et autres
Publié: (2025)

On the Thinking-Language Modeling Gap in Large Language Models
par: Liu, Chenxi, et autres
Publié: (2025)

A Contextualized BERT model for Knowledge Graph Completion
par: Gul, Haji, et autres
Publié: (2024)

Reconstruct Your Previous Conversations! Comprehensively Investigating Privacy Leakage Risks in Conversations with GPT Models
par: Chu, Junjie, et autres
Publié: (2024)

Breaking the Benchmark: Revealing LLM Bias via Minimal Contextual Augmentation
par: Miandoab, Kaveh Eskandari, et autres
Publié: (2025)

AMGPT: a Large Language Model for Contextual Querying in Additive Manufacturing
par: Chandrasekhar, Achuth, et autres
Publié: (2024)

MEG: Medical Knowledge-Augmented Large Language Models for Question Answering
par: Cabello, Laura, et autres
Publié: (2024)

Memory-Efficient Differentially Private Training with Gradient Random Projection
par: Mulrooney, Alex, et autres
Publié: (2025)

Personalizing Large Language Models using Retrieval Augmented Generation and Knowledge Graph
par: Prahlad, Deeksha, et autres
Publié: (2025)

ISACL: Internal State Analyzer for Copyrighted Training Data Leakage
par: Zhang, Guangwei, et autres
Publié: (2025)

TokenShapley: Token Level Context Attribution with Shapley Value
par: Xiao, Yingtai, et autres
Publié: (2025)

Unlocking the Potentials of Retrieval-Augmented Generation for Diffusion Language Models
par: Yu, Chuanyue, et autres
Publié: (2026)

KVPR: Efficient LLM Inference with I/O-Aware KV Cache Partial Recomputation
par: Jiang, Chaoyi, et autres
Publié: (2024)

HarmAug: Effective Data Augmentation for Knowledge Distillation of Safety Guard Models
par: Lee, Seanie, et autres
Publié: (2024)

CASCADE Your Datasets for Cross-Mode Knowledge Retrieval of Language Models
par: Zhou, Runlong, et autres
Publié: (2025)