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arXivPrivacy

What Gradients Add to Text Leakage in Split Language Models, Counted per Token and per Document

Split-language-model gradients boost token recovery to 97.38% and document reconstruction to 37.77%, so split traffic requires per-token and per-document leakage reporting.

Georgios Politis, Evangelos Pappas

Published Oct 2, 2026 · ▲ 8 on Hugging Face

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AI panel: 13 of 20 reviewers recommend it
lenient 5/5
medium 6/10
strict 2/5
70%Highly rated
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NAACL 2025Privacy

Protecting Privacy in Multimodal Large Language Models with MLLMU-Bench

MLLMU-Bench evaluates privacy risks in multimodal large language models via standardized leakage and inference benchmarks.

Zheyuan Liu, Guangyao Dou, Mengzhao Jia, Zhaoxuan Tan and 3 more

Published 2025 · 5 citations

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AI panel: 5 of 20 reviewers recommend it
lenient 3/5
medium 2/10
strict 0/5
78%Highly rated
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ICML 2024Privacy

Verification of Machine Unlearning is Fragile

Verification of machine unlearning is fragile because model providers can circumvent verification strategies and retain supposedly unlearned data.

Binchi Zhang, Zihan Chen, Cong Shen, Jundong Li

Published Aug 1, 2024 · 0 citations

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AI panel: 11 of 20 reviewers recommend it
lenient 5/5
medium 5/10
strict 1/5
45%Niche pick
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NeurIPS 2026U New South WalesU SydneyPrivacy

On the Price of Privacy for Language Identification and Generation

Xiaoyu Li, Andi Han, Jiaojiao Jiang, Junbin Gao

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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lenient 0/5
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57%Worth a look
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NeurIPS 2026SoutheastTongjiPrivacy

Privacy Meets Hierarchy: Differentially Private Distributed Trilevel Learning

Yang Jiao, Kai Yang

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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lenient 1/5
medium 0/10
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NeurIPS 2026Morph ResearchPrivacy

DP-EGGROLL: Centered Fitness-Vector Privatization for Backprop-Free Differentially Private Optimization

David T Zagardo

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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lenient 0/5
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67%Highly rated
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NeurIPS 2026Pohang University of Science andGwangju Institute of Science andPOSTECHPrivacy

I2V-DETACH: Source Grounding Detachment for Unauthorized Image-to-Video Generation

Chanhui Lee, Yeonghwan Song, Yewon Kang, Jeany Son

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 2 of 20 reviewers recommend it
lenient 2/5
medium 0/10
strict 0/5
57%Worth a look
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NeurIPS 2026PurduePrivacy

Tail Wags the Model: Generalization and Membership Privacy Trade-offs of Sharpness-Aware Minimization

Young In Kim, Rajiv Khanna

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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AI panel: 1 of 20 reviewers recommend it
lenient 1/5
medium 0/10
strict 0/5
57%Worth a look
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NeurIPS 2026Brigham YoungFlorida StatePrivacy

GraphIP–Bench: How Hard Is It to Steal a Graph Neural Network, and Can We Stop It?

Kaixiang Zhao, Bolin Shen, Yuyang Dai, Shayok Chakraborty and 1 more

Atlanta Poster Session 3, Thu, Dec 10, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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NeurIPS 2026Visa ResearchVISA ResearchU FloridaVISAPrivacy

Privacy-Preserving Retrieval-Augmented Generation with Plausible Deniability

Wenxuan Bao, Shan Jin, Vincent Bindschaedler, Yiwei Cai

Atlanta Poster Session 1, Wed, Dec 9, 10:00 AM–1:00 PM, Hall C1 · Published 2026

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lenient 1/5
medium 0/10
strict 0/5
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NeurIPS 2026SpotlightU CopenhagenPrivacy

Optimal Rates for Adaptive Private $k$-PCA

Johanna Düngler, Amartya Sanyal

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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lenient 0/5
medium 0/10
strict 0/5
67%Highly rated
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NeurIPS 2026CISPA Helmholtz Center for InforCISPAPrivacy

Benchmarking Membership Privacy Risks in Preference-Based LLM Post-Training

Lorenzo Rossi, Kaif Shaikh, Franziska Boenisch, Adam Dziedzic

Sydney Poster Session 5, Thu, Dec 10, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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AI panel: 2 of 20 reviewers recommend it
lenient 1/5
medium 1/10
strict 0/5
67%Highly rated
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NeurIPS 2026CISPA Helmholtz Center for InforCISPAPrivacy

Auditing Privacy Leakage in Tabular Foundation Model Embeddings

Xun Wang, Adam Dziedzic, Michael Backes, Franziska Boenisch

Sydney Poster Session 3, Wed, Dec 9, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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lenient 1/5
medium 1/10
strict 0/5
69%Highly rated
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NeurIPS 2026U North Carolina at Chapel HillArizona State University of North Carolina atPrivacy

Guarding the Life Code: Preserving Membership Privacy in Genomic Foundation Models

Xinyu Zhao, Jinhao Duan, Zhen Tan, Tianlong Chen

Atlanta Poster Session 6, Fri, Dec 11, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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AI panel: 3 of 20 reviewers recommend it
lenient 2/5
medium 1/10
strict 0/5
57%Worth a look
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NeurIPS 2026ZhejiangThe State Key Laboratory of BlocIndependentKAUSTKing Abdullah University of SciePrivacy

Ask in the Crowd: Differentially Private LLM Inference via Dummy-Augmented Shuffling

Zhihao Liu, Zixiong Guo, Shuo Shao, Yu He and 4 more

Sydney Poster Session 4, Wed, Dec 9, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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lenient 1/5
medium 0/10
strict 0/5
69%Highly rated
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NeurIPS 2026U OuluELLIS Institute Finland & UnPrivacy

How Private is Private? A Comparative Study for Face De-Identification

Hui Wei, Hao Yu, Hui Kuurila-Zhang, Guoying Zhao

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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AI panel: 3 of 20 reviewers recommend it
lenient 2/5
medium 1/10
strict 0/5
57%Worth a look
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NeurIPS 2026Dalian MaritimeGuangzhouOcean University of ChinaNortheasternPrivacy

LDPCache: Locally Differentially Private Multi-Query Processing with Cache Optimization for Large Language Models

Haoqiang Shi, Ning Wang, Chuan He, Qian Ma and 4 more

Sydney Poster Session 1, Tue, Dec 8, 10:00 AM–1:00 PM, Hall 1-4 · Published 2026

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lenient 1/5
medium 0/10
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NeurIPS 2026RutgersMeta FAIRPrivacy

Towards Hyperparameter Transfer for Differentially Private Optimization

Tianze Wang, Zhiqi Bu, Linjun Zhang

Atlanta Poster Session 2, Wed, Dec 9, 4:30 PM–7:30 PM, Hall C1 · Published 2026

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NeurIPS 2026Aerospace Information Research IShandongAerospace Information Research IAerospace Information Research IPrivacy

Auditing Single-Query Recoverability in Self-Supervised Representations

zirui wang, Guangqiang He, PangWu, Peng Wang and 4 more

Sydney Poster Session 2, Tue, Dec 8, 5:00 PM–8:00 PM, Hall 1-4 · Published 2026

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NeurIPS 2026Huazhong University of Science aBeijing University of Posts and The Hong Kong PolytechnicU CambridgePrivacy

Personalized Safety in Federated Fine-Tuning of Large Language Models

Tianzhe Xiao, Gaozhuo Liu, Yichen Li, Haozhao Wang and 3 more

Paris Poster Session 4, Thu, Dec 10, 5:30 PM–7:30 PM, Paris Poster Hall · Published 2026

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AI panel: 1 of 20 reviewers recommend it
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