Saved in:
| Main Authors: | Takahashi, Hiromu, Ishihara, Shotaro |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | https://arxiv.org/abs/2510.23074 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
Tab-MIA: A Benchmark Dataset for Membership Inference Attacks on Tabular Data in LLMs
by: German, Eyal, et al.
Published: (2025)
by: German, Eyal, et al.
Published: (2025)
DocMIA: Document-Level Membership Inference Attacks against DocVQA Models
by: Nguyen, Khanh, et al.
Published: (2025)
by: Nguyen, Khanh, et al.
Published: (2025)
Membership Inference Attacks Against In-Context Learning
by: Wen, Rui, et al.
Published: (2024)
by: Wen, Rui, et al.
Published: (2024)
SoK: Membership Inference Attacks on LLMs are Rushing Nowhere (and How to Fix It)
by: Meeus, Matthieu, et al.
Published: (2024)
by: Meeus, Matthieu, et al.
Published: (2024)
ImpMIA: Leveraging Implicit Bias for Membership Inference Attack
by: Golbari, Yuval, et al.
Published: (2025)
by: Golbari, Yuval, et al.
Published: (2025)
AutoMIA: Improved Baselines for Membership Inference Attack via Agentic Self-Exploration
by: Liu, Ruhao, et al.
Published: (2026)
by: Liu, Ruhao, et al.
Published: (2026)
SeqMIA: Sequential-Metric Based Membership Inference Attack
by: Li, Hao, et al.
Published: (2024)
by: Li, Hao, et al.
Published: (2024)
Membership Inference Attacks and Privacy in Topic Modeling
by: Manzonelli, Nico, et al.
Published: (2024)
by: Manzonelli, Nico, et al.
Published: (2024)
Towards Label-Only Membership Inference Attack against Pre-trained Large Language Models
by: He, Yu, et al.
Published: (2025)
by: He, Yu, et al.
Published: (2025)
Blind Baselines Beat Membership Inference Attacks for Foundation Models
by: Das, Debeshee, et al.
Published: (2024)
by: Das, Debeshee, et al.
Published: (2024)
Tag&Tab: Pretraining Data Detection in Large Language Models Using Keyword-Based Membership Inference Attack
by: Antebi, Sagiv, et al.
Published: (2025)
by: Antebi, Sagiv, et al.
Published: (2025)
Quantifying Memorization and Detecting Training Data of Pre-trained Language Models using Japanese Newspaper
by: Ishihara, Shotaro, et al.
Published: (2024)
by: Ishihara, Shotaro, et al.
Published: (2024)
MIA-Tuner: Adapting Large Language Models as Pre-training Text Detector
by: Fu, Wenjie, et al.
Published: (2024)
by: Fu, Wenjie, et al.
Published: (2024)
MIA-EPT: Membership Inference Attack via Error Prediction for Tabular Data
by: German, Eyal, et al.
Published: (2025)
by: German, Eyal, et al.
Published: (2025)
Synthetic Data Can Mislead Evaluations: Membership Inference as Machine Text Detection
by: Naseh, Ali, et al.
Published: (2025)
by: Naseh, Ali, et al.
Published: (2025)
On the Effectiveness of Membership Inference in Targeted Data Extraction from Large Language Models
by: Sahili, Ali Al, et al.
Published: (2025)
by: Sahili, Ali Al, et al.
Published: (2025)
Window-based Membership Inference Attacks Against Fine-tuned Large Language Models
by: Chen, Yuetian, et al.
Published: (2026)
by: Chen, Yuetian, et al.
Published: (2026)
P-MIA: A Profiled-Based Membership Inference Attack on Cognitive Diagnosis Models
by: Hou, Mingliang, et al.
Published: (2025)
by: Hou, Mingliang, et al.
Published: (2025)
ReproMIA: A Comprehensive Analysis of Model Reprogramming for Proactive Membership Inference Attacks
by: Huang, Chihan, et al.
Published: (2026)
by: Huang, Chihan, et al.
Published: (2026)
Automated Membership Inference Attacks: Discovering MIA Signal Computations using LLM Agents
by: Tran, Toan, et al.
Published: (2026)
by: Tran, Toan, et al.
Published: (2026)
The Hidden Cost of Modeling P(X): Vulnerability to Membership Inference Attacks in Generative Text Classifiers
by: Makroo, Owais, et al.
Published: (2025)
by: Makroo, Owais, et al.
Published: (2025)
Did the Neurons Read your Book? Document-level Membership Inference for Large Language Models
by: Meeus, Matthieu, et al.
Published: (2023)
by: Meeus, Matthieu, et al.
Published: (2023)
A Bayesian Approach to Membership Inference for Statistical Release
by: Oakley, Lisa, et al.
Published: (2026)
by: Oakley, Lisa, et al.
Published: (2026)
LoRA-Leak: Membership Inference Attacks Against LoRA Fine-tuned Language Models
by: Ran, Delong, et al.
Published: (2025)
by: Ran, Delong, et al.
Published: (2025)
FedMIA: An Effective Membership Inference Attack Exploiting "All for One" Principle in Federated Learning
by: Zhu, Gongxi, et al.
Published: (2024)
by: Zhu, Gongxi, et al.
Published: (2024)
E-MIA: Exam-Style Black-Box Membership Inference Attacks against RAG Systems
by: Guan, Zelin, et al.
Published: (2026)
by: Guan, Zelin, et al.
Published: (2026)
Practical Membership Inference Attacks against Fine-tuned Large Language Models via Self-prompt Calibration
by: Fu, Wenjie, et al.
Published: (2023)
by: Fu, Wenjie, et al.
Published: (2023)
A Simple and Efficient Jailbreak Method Exploiting LLMs' Helpfulness
by: Luo, Xuan, et al.
Published: (2025)
by: Luo, Xuan, et al.
Published: (2025)
LexiMark: Robust Watermarking via Lexical Substitutions to Enhance Membership Verification of an LLM's Textual Training Data
by: German, Eyal, et al.
Published: (2025)
by: German, Eyal, et al.
Published: (2025)
Context-Aware Membership Inference Attacks against Pre-trained Large Language Models
by: Chang, Hongyan, et al.
Published: (2024)
by: Chang, Hongyan, et al.
Published: (2024)
Membership Inference Attacks on LLM-based Recommender Systems
by: He, Jiajie, et al.
Published: (2025)
by: He, Jiajie, et al.
Published: (2025)
Auditing Data Membership in Reinforcement Learning With Verifiable Rewards
by: Liu, Yule, et al.
Published: (2025)
by: Liu, Yule, et al.
Published: (2025)
Waterfall: Framework for Robust and Scalable Text Watermarking and Provenance for LLMs
by: Lau, Gregory Kang Ruey, et al.
Published: (2024)
by: Lau, Gregory Kang Ruey, et al.
Published: (2024)
Efficient and Stealthy Jailbreak Attacks via Adversarial Prompt Distillation from LLMs to SLMs
by: Li, Xiang, et al.
Published: (2025)
by: Li, Xiang, et al.
Published: (2025)
Riddle Me This! Stealthy Membership Inference for Retrieval-Augmented Generation
by: Naseh, Ali, et al.
Published: (2025)
by: Naseh, Ali, et al.
Published: (2025)
STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings
by: Rastogi, Saksham, et al.
Published: (2025)
by: Rastogi, Saksham, et al.
Published: (2025)
Membership Inference Attacks against Large Vision-Language Models
by: Li, Zhan, et al.
Published: (2024)
by: Li, Zhan, et al.
Published: (2024)
Res-MIA: A Training-Free Resolution-Based Membership Inference Attack on Federated Learning Models
by: Zare, Mohammad, et al.
Published: (2026)
by: Zare, Mohammad, et al.
Published: (2026)
SecFormer: Fast and Accurate Privacy-Preserving Inference for Transformer Models via SMPC
by: Luo, Jinglong, et al.
Published: (2024)
by: Luo, Jinglong, et al.
Published: (2024)
Stop Tracking Me! Proactive Defense Against Attribute Inference Attack in LLMs
by: Yan, Dong, et al.
Published: (2026)
by: Yan, Dong, et al.
Published: (2026)
Similar Items
-
Tab-MIA: A Benchmark Dataset for Membership Inference Attacks on Tabular Data in LLMs
by: German, Eyal, et al.
Published: (2025) -
DocMIA: Document-Level Membership Inference Attacks against DocVQA Models
by: Nguyen, Khanh, et al.
Published: (2025) -
Membership Inference Attacks Against In-Context Learning
by: Wen, Rui, et al.
Published: (2024) -
SoK: Membership Inference Attacks on LLMs are Rushing Nowhere (and How to Fix It)
by: Meeus, Matthieu, et al.
Published: (2024) -
ImpMIA: Leveraging Implicit Bias for Membership Inference Attack
by: Golbari, Yuval, et al.
Published: (2025)