On the public citation graph

Privacy Preserving Prompt Engineering: A Survey

0 signed · 143 inferred · view as graph

Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

Is this your work? Sign in with ORCID and put your name on the claims that are yours.

Claim with ORCID

Reference health. See whether every reference in this work resolves to a known work and none has been retracted — and get a dated CiteStamped badge you can embed.

See reference health

What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/11681878_14openalex-snapshot

Calibrating Noise to Sensitivity in Private Data Analysis

inferredcites →https://doi.org/10.1007/978-3-030-87199-4_33openalex-snapshot

Personalized Retrogress-Resilient Framework for Real-World Medical Federated Learning

inferredcites →https://doi.org/10.1007/978-3-031-19827-4_41openalex-snapshot

Visual Prompt Tuning

inferredcites →https://doi.org/10.1007/978-3-031-70552-6_12openalex-snapshot

Privacy-Aware Document Visual Question Answering

inferredcites →https://doi.org/10.1007/978-3-540-30115-8_22openalex-snapshot

The Enron Corpus: A New Dataset for Email Classification Research

inferredcites →https://doi.org/10.1007/978-3-642-15561-1_16openalex-snapshot

Adapting Visual Category Models to New Domains

inferredcites →https://doi.org/10.1007/s10579-005-7880-9openalex-snapshot

Annotating Expressions of Opinions and Emotions in Language

inferredcites →https://doi.org/10.1007/s11263-022-01653-1openalex-snapshot

Learning to Prompt for Vision-Language Models

inferredcites →https://doi.org/10.1007/s11431-020-1647-3openalex-snapshot

Pre-trained models for natural language processing: A survey

inferredcites →https://doi.org/10.1007/s41060-021-00285-xopenalex-snapshot

Anonymization of German financial documents using neural network-based language models with contextual word representations

inferredcites →https://doi.org/10.1016/j.aiopen.2021.08.002openalex-snapshot

Pre-trained models: Past, present and future

inferredcites →https://doi.org/10.1016/j.hcc.2024.100211openalex-snapshot

A survey on large language model (LLM) security and privacy: The Good, The Bad, and The Ugly

inferredcites →https://doi.org/10.1038/s41597-022-01721-8openalex-snapshot

MedMNIST v2 - A large-scale lightweight benchmark for 2D and 3D biomedical image classification

inferredcites →https://doi.org/10.1080/01621459.1965.10480775openalex-snapshot

Randomized Response: A Survey Technique for Eliminating Evasive Answer Bias

inferredcites →https://doi.org/10.1109/bigdata62323.2024.10826053openalex-snapshot

DP-TabICL: In-Context Learning with Differentially Private Tabular Data

inferredcites →https://doi.org/10.1109/csf.2018.00026openalex-snapshot

Invited Paper: Local Differential Privacy on Metric Spaces: Optimizing the Trade-Off with Utility

inferredcites →https://doi.org/10.1109/focs.2007.66openalex-snapshot

Mechanism Design via Differential Privacy

inferredcites →https://doi.org/10.1109/iccv.2019.00149openalex-snapshot

Moment Matching for Multi-Source Domain Adaptation

inferredcites →https://doi.org/10.1109/iccv51070.2023.00476openalex-snapshot

Exploring the Benefits of Visual Prompting in Differential Privacy

inferredcites →https://doi.org/10.1109/iccv51070.2023.01755openalex-snapshot

Efficient Model Personalization in Federated Learning via Client-Specific Prompt Generation

inferredcites →https://doi.org/10.1109/sp46215.2023.10179300openalex-snapshot

Analyzing Leakage of Personally Identifiable Information in Language Models

inferredcites →https://doi.org/10.1109/tmc.2023.3302410openalex-snapshot

PromptFL: Let Federated Participants Cooperatively Learn Prompts Instead of Models – Federated Learning in Age of Foundation Model

inferredcites →https://doi.org/10.1109/tpami.2024.3369699openalex-snapshot

Vision-Language Models for Vision Tasks: A Survey

inferredcites →https://doi.org/10.1137/090756090openalex-snapshot

What Can We Learn Privately?

inferredcites →https://doi.org/10.1137/1.9781611977653.ch99openalex-snapshot

TEM: High Utility Metric Differential Privacy on Text

inferredcites →https://doi.org/10.1145/1250790.1250803openalex-snapshot

Smooth sensitivity and sampling in private data analysis

inferredcites →https://doi.org/10.1145/1536414.1536466openalex-snapshot

Differential privacy and robust statistics

inferredcites →https://doi.org/10.1145/2414456.2414474openalex-snapshot

On sampling, anonymization, and differential privacy or, k -anonymization meets differential privacy

inferredcites →https://doi.org/10.1145/2976749.2978318openalex-snapshot

Deep Learning with Differential Privacy

inferredcites →https://doi.org/10.1145/3035918openalex-snapshot

Proceedings of the 2017 ACM International Conference on Management of Data

inferredcites →https://doi.org/10.1145/3035918.3064047openalex-snapshot

Bolt-on Differential Privacy for Scalable Stochastic Gradient Descent-based Analytics

inferredcites →https://doi.org/10.1145/3195970.3196023openalex-snapshot

Deepsecure

inferredcites →https://doi.org/10.1145/3336191.3371856openalex-snapshot

Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations

inferredcites →https://doi.org/10.1145/3397271.3401260openalex-snapshot

Towards Differentially Private Text Representations

inferredcites →https://doi.org/10.1145/3460120.3484734openalex-snapshot

Differential Privacy for Directional Data

inferredcites →https://doi.org/10.1145/3543507.3583512openalex-snapshot

Sanitizing Sentence Embeddings (and Labels) for Local Differential Privacy

inferredcites →https://doi.org/10.1145/3548606openalex-snapshot

Proceedings of the 2022 ACM SIGSAC Conference on Computer and Communications Security

inferredcites →https://doi.org/10.1145/3560815openalex-snapshot

Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processing

inferredcites →https://doi.org/10.1145/3576915openalex-snapshot

Proceedings of the 2023 ACM SIGSAC Conference on Computer and Communications Security

inferredcites →https://doi.org/10.1145/3576915.3616592openalex-snapshot

DP-Forward: Fine-tuning and Inference on Language Models with Differential Privacy in Forward Pass

inferredcites →https://doi.org/10.1145/3589334openalex-snapshot

Proceedings of the ACM Web Conference 2024

inferredcites →https://doi.org/10.1145/3624724openalex-snapshot

Talking about Large Language Models

inferredcites →https://doi.org/10.1145/3712001openalex-snapshot

Security and Privacy Challenges of Large Language Models: A Survey

inferredcites →https://doi.org/10.1145/3727339openalex-snapshot

A Primer on Pretrained Multilingual Language Models

inferredcites →https://doi.org/10.1561/0400000042openalex-snapshot

The Algorithmic Foundations of Differential Privacy

inferredcites →https://doi.org/10.18653/v1/2020.emnlp-main.346openalex-snapshot

AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts

inferredcites →https://doi.org/10.18653/v1/2021.emnlp-main.243openalex-snapshot

The Power of Scale for Parameter-Efficient Prompt Tuning

inferredcites →https://doi.org/10.18653/v1/2021.emnlp-main.628openalex-snapshot

CAPE: Context-Aware Private Embeddings for Private Language Learning

inferredcites →https://doi.org/10.18653/v1/2021.findings-acl.337openalex-snapshot

Differential Privacy for Text Analytics via Natural Text Sanitization

inferredcites →https://doi.org/10.18653/v1/2022.acl-long.238openalex-snapshot

Sentence-level Privacy for Document Embeddings

inferredcites →https://doi.org/10.18653/v1/2022.emnlp-main.572openalex-snapshot

TextFusion: Privacy-Preserving Pre-trained Model Inference via Token Fusion

inferredcites →https://doi.org/10.18653/v1/2022.findings-acl.277openalex-snapshot

THE-X: Privacy-Preserving Transformer Inference with Homomorphic Encryption

inferredcites →https://doi.org/10.18653/v1/2023.emnlp-main.319openalex-snapshot

LLM-Adapters: An Adapter Family for Parameter-Efficient Fine-Tuning of Large Language Models

inferredcites →https://doi.org/10.18653/v1/2023.emnlp-main.921openalex-snapshot

Privacy Implications of Retrieval-Based Language Models

inferredcites →https://doi.org/10.18653/v1/2023.findings-acl.132openalex-snapshot

Nonparametric Masked Language Modeling

inferredcites →https://doi.org/10.18653/v1/2023.findings-acl.337openalex-snapshot

TextObfuscator: Making Pre-trained Language Model a Privacy Protector via Obfuscating Word Representations

inferredcites →https://doi.org/10.18653/v1/2023.findings-acl.355openalex-snapshot

A Customized Text Sanitization Mechanism with Differential Privacy

inferredcites →https://doi.org/10.18653/v1/2023.findings-acl.779openalex-snapshot

Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation

inferredcites →https://doi.org/10.18653/v1/2023.findings-emnlp.566openalex-snapshot

Locally Differentially Private Document Generation Using Zero Shot Prompting

inferredcites →https://doi.org/10.18653/v1/2023.trustnlp-1.23openalex-snapshot

Training Data Extraction From Pre-trained Language Models: A Survey

inferredcites →https://doi.org/10.18653/v1/2024.acl-long.235openalex-snapshot

CoGenesis: A Framework Collaborating Large and Small Language Models for Secure Context-Aware Instruction Following

inferredcites →https://doi.org/10.18653/v1/2024.findings-acl.769openalex-snapshot

Differentially Private Knowledge Distillation via Synthetic Text Generation

inferredcites →https://doi.org/10.18653/v1/2024.findings-eacl.33openalex-snapshot

Differentially Private Natural Language Models: Recent Advances and Future Directions

inferredcites →https://doi.org/10.18653/v1/2025.emnlp-main.9openalex-snapshot

Comparing Specialised Small and General Large Language Models on Text Classification: 100 Labelled Samples to Achieve Break-Even Performance

inferredcites →https://doi.org/10.18653/v1/d13-1170openalex-snapshot

Recursive Deep Models for Semantic Compositionality Over a Sentiment Treebank

inferredcites →https://doi.org/10.18653/v1/d19-5409openalex-snapshot

SAMSum Corpus: A Human-annotated Dialogue Dataset for Abstractive Summarization

inferredcites →https://doi.org/10.21437/interspeech.2012-563openalex-snapshot

A conversational movie search system based on conditional random fields

inferredcites →https://doi.org/10.2307/40041279openalex-snapshot

A Taxonomy of Privacy

inferredcites →https://doi.org/10.3115/1072228.1072378openalex-snapshot

Learning question classifiers

inferredcites →https://doi.org/10.3233/icg-2014-37208openalex-snapshot

ENDGAME ANALYSIS OF DOU SHOU QI

inferredcites →https://doi.org/10.3390/s20247030openalex-snapshot

A Comprehensive Survey on Local Differential Privacy toward Data Statistics and Analysis

inferredcites →https://doi.org/10.35111/mwxc-vh88openalex-snapshot

ACE 2005 Multilingual Training Corpus

inferredcites →https://doi.org/10.3929/ethz-b-000720050openalex-snapshot

Beyond Memorization: Violating Privacy Via Inference with Large Language Models

inferredcites →https://doi.org/10.4230/lipics.cosit.2022.18openalex-snapshot

AI-Assisted Pipeline for Dynamic Generation of Trustworthy Health Supplement Content at Scale

inferredcites →https://doi.org/10.4230/oasics.commit2data.3openalex-snapshot

BLOOM: A 176B-Parameter Open-Access Multilingual Language Model

inferredcites →https://doi.org/10.48550/arxiv.1208.0219openalex-snapshot

Functional Mechanism: Regression Analysis under Differential Privacy

inferredcites →https://doi.org/10.48550/arxiv.1509.01626openalex-snapshot

Character-level Convolutional Networks for Text Classification

inferredcites →https://doi.org/10.48550/arxiv.1804.07461openalex-snapshot

GLUE: A Multi-Task Benchmark and Analysis Platform for Natural Language Understanding

inferredcites →https://doi.org/10.48550/arxiv.1911.00172openalex-snapshot

Generalization through Memorization: Nearest Neighbor Language Models

inferredcites →https://doi.org/10.48550/arxiv.2009.12756openalex-snapshot

Answering Complex Open-Domain Questions with Multi-Hop Dense Retrieval

inferredcites →https://doi.org/10.48550/arxiv.2010.11947openalex-snapshot

A Differentially Private Text Perturbation Method Using a Regularized Mahalanobis Metric

inferredcites →https://doi.org/10.48550/arxiv.2101.00190openalex-snapshot

Prefix-Tuning: Optimizing Continuous Prompts for Generation

inferredcites →https://doi.org/10.48550/arxiv.2106.09685openalex-snapshot

LoRA Fine-Tuning of a 3B Code LLM for Algorithmic Efficiency

inferredcites →https://doi.org/10.48550/arxiv.2107.00778openalex-snapshot

On Bridging Generic and Personalized Federated Learning for Image Classification

inferredcites →https://doi.org/10.48550/arxiv.2201.11903openalex-snapshot

BNAI, NO-TOKEN, and MIND-UNITY: Pillars of a Systemic Revolution in Artificial Intelligence

inferredcites →https://doi.org/10.48550/arxiv.2205.10625openalex-snapshot

Least-to-Most Prompting Enables Complex Reasoning in Large Language Models

inferredcites →https://doi.org/10.48550/arxiv.2209.10505openalex-snapshot

Text Revealer: Private Text Reconstruction via Model Inversion Attacks against Transformers

inferredcites →https://doi.org/10.48550/arxiv.2211.01786openalex-snapshot

Crosslingual Generalization through Multitask Finetuning

inferredcites →https://doi.org/10.48550/arxiv.2212.12017openalex-snapshot

OPT-IML: Scaling Language Model Instruction Meta Learning through the Lens of Generalization

inferredcites →https://doi.org/10.48550/arxiv.2302.13971openalex-snapshot

LLaMA: Open and Efficient Foundation Language Models

inferredcites →https://doi.org/10.48550/arxiv.2304.06762openalex-snapshot

Shall We Pretrain Autoregressive Language Models with Retrieval? A Comprehensive Study

inferredcites →https://doi.org/10.48550/arxiv.2305.15594openalex-snapshot

Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models

inferredcites →https://doi.org/10.48550/arxiv.2306.01684openalex-snapshot

Harnessing large-language models to generate private synthetic text

inferredcites →https://doi.org/10.48550/arxiv.2306.08223openalex-snapshot

Protecting User Privacy in Remote Conversational Systems: A Privacy-Preserving framework based on text sanitization

inferredcites →https://doi.org/10.48550/arxiv.2309.03057openalex-snapshot

Hide and Seek (HaS): A Lightweight Framework for Prompt Privacy Protection

inferredcites →https://doi.org/10.48550/arxiv.2309.11765openalex-snapshot

Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation

inferredcites →https://doi.org/10.48550/arxiv.2309.17157openalex-snapshot

LatticeGen: A Cooperative Framework which Hides Generated Text in a Lattice for Privacy-Aware Generation on Cloud

inferredcites →https://doi.org/10.48550/arxiv.2311.15792openalex-snapshot

Rethinking Privacy in Machine Learning Pipelines from an Information Flow Control Perspective

inferredcites →https://doi.org/10.48550/arxiv.2312.03724openalex-snapshot

DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer

inferredcites →https://doi.org/10.48550/arxiv.2402.05868openalex-snapshot

EmojiPrompt: Generative Prompt Obfuscation for Privacy-Preserving Communication with Cloud-based LLMs

inferredcites →https://doi.org/10.48550/arxiv.2402.08227openalex-snapshot

Privacy-Preserving Language Model Inference with Instance Obfuscation

inferredcites →https://doi.org/10.48550/arxiv.2403.01749openalex-snapshot

Differentially Private Synthetic Data via Foundation Model APIs 2: Text

inferredcites →https://doi.org/10.48550/arxiv.2403.09720openalex-snapshot

Fine-tuning vs Prompting, Can Language Models Understand Human Values?

inferredcites →https://doi.org/10.52202/068431-0808openalex-snapshot

SeqPATE: Differentially Private Text Generation Via Knowledge Distillation

inferredcites →https://doi.org/10.52202/068431-2704openalex-snapshot

Deep Bidirectional Language-Knowledge Graph Pretraining

inferredcites →https://doi.org/10.52202/075280-1361openalex-snapshot

DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models

inferredcites →https://doi.org/10.52202/075280-2433openalex-snapshot

Large Language Model as Attributed Training Data Generator: A Tale of Diversity and Bias

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1007/978-3-031-72440-4_16openalex-snapshot

Comparative Analysis: User Interactions in Public and Private Digital Libraries Datasets

inferred← citeshttps://doi.org/10.1007/978-981-95-4423-3_18openalex-snapshot

AI Support for the Marking of Written Student Papers: A Legal View

inferred← citeshttps://doi.org/10.1016/b978-0-443-44344-2.00003-0openalex-snapshot

Foundations and frameworks for large language models: Concepts and deployment strategies

inferred← citeshttps://doi.org/10.1016/j.actpsy.2025.105796openalex-snapshot

From academics to Aidemics: Unpacking the human–AI symbiosis in higher education

inferred← citeshttps://doi.org/10.1016/j.aei.2026.105176openalex-snapshot

Event logic graph-augmented generation for interpretable urban waterlogging emergency decision-making

inferred← citeshttps://doi.org/10.1016/j.cosrev.2026.100979openalex-snapshot

A comprehensive survey of prompt engineering and context engineering techniques in large language models

inferred← citeshttps://doi.org/10.1016/j.iotcps.2026.03.001openalex-snapshot

Securing LLM agents: From prompt sanitization to autonomous red teaming and beyond

inferred← citeshttps://doi.org/10.1016/j.ipm.2025.104505openalex-snapshot

Privacy protection in RAG: A novel method and evaluation framework

inferred← citeshttps://doi.org/10.1016/j.neucom.2026.134973openalex-snapshot

Load balancing for large language model inference serving: A control and learning oriented survey

inferred← citeshttps://doi.org/10.1016/j.rcim.2026.103313openalex-snapshot

Leveraging large and small model collaboration for advanced automation in smart manufacturing

inferred← citeshttps://doi.org/10.1049/itr2.70178openalex-snapshot

SEDM: A Safety‐Enhanced Decision‐Making Framework for Autonomous Driving by Integrating Large Language Models and XGBoost

inferred← citeshttps://doi.org/10.1093/jamiaopen/ooag135openalex-snapshot

Scalable extraction of social determinants of health from clinical notes in a sepsis cohort using instruction-tuned language models

inferred← citeshttps://doi.org/10.1109/bigdataservice70481.2026.00046openalex-snapshot

A Local Middleware for Privacy-Preserving LLM Inference via Reversible Entity Substitution

inferred← citeshttps://doi.org/10.1109/defi67526.2025.11551605openalex-snapshot

SecurePrep: A Human-in-the-Loop Toolkit for Privacy-Preserving Prompt Engineering in the LLM Era

inferred← citeshttps://doi.org/10.1109/edgecom66327.2025.00036openalex-snapshot

A Survey of Privacy Preservation Techniques for Large Language Models

inferred← citeshttps://doi.org/10.1109/ichcai70183.2026.11607672openalex-snapshot

Human-Centric, Privacy-Aware Rag Architecture for Higher Education: Design Principles and Governance-Aware Evaluation

inferred← citeshttps://doi.org/10.1109/icnp65844.2025.11192338openalex-snapshot

PrivMLLM: Efficient Three-Party Multimodal Large Language Model Secure Inference Supported Prompt Privacy

inferred← citeshttps://doi.org/10.1109/icscan66520.2026.11588366openalex-snapshot

Self-Healing Cyber Defence System Legal Risk Detector for AI Model

inferred← citeshttps://doi.org/10.1109/ism66958.2025.00011openalex-snapshot

Exploring Privacy and Security Risks in LLMs: Data Leakage, Prompt Injection, and Membership Inference

inferred← citeshttps://doi.org/10.1109/jsac.2025.3647412openalex-snapshot

Covert Prompt Transmission for Secure Large Language Model Services

inferred← citeshttps://doi.org/10.1109/tai.2025.3626467openalex-snapshot

A Systematic Literature Review on SWOT Analysis of Prompt Engineering Techniques

inferred← citeshttps://doi.org/10.1109/tifs.2026.3667458openalex-snapshot

Risk-Aware Privacy Preservation for LLM Inference

inferred← citeshttps://doi.org/10.1109/tits.2026.3651004openalex-snapshot

A Survey on the Application of Large Language Models in Scenario-Based Testing of Automated Driving Systems

inferred← citeshttps://doi.org/10.1145/3664476.3669926openalex-snapshot

Just Rewrite It Again: A Post-Processing Method for Enhanced Semantic Similarity and Privacy Preservation of Differentially Private Rewritten Text

inferred← citeshttps://doi.org/10.1145/3701625.3701675openalex-snapshot

Investigating Software Development Teams Members' Perceptions of Data Privacy in the Use of Large Language Models (LLMs)

inferred← citeshttps://doi.org/10.1145/3770855.3817665openalex-snapshot

Privacy-Aware Decoding: Mitigating Privacy Leakage of Large Language Models in Retrieval-Augmented Generation

inferred← citeshttps://doi.org/10.1145/3773078.3831733openalex-snapshot

Membership Inference Attacks on In-Context Learning Recommendation

inferred← citeshttps://doi.org/10.1145/3786169.3788400openalex-snapshot

PrivAuto: Practical Insights of On-Device Privacy-Preserving Agentic Systems for Mobile GUI Automation

inferred← citeshttps://doi.org/10.1177/1088467x261471261openalex-snapshot

Activation-based efficient routing for retrieval-augmented generation in LLMs

inferred← citeshttps://doi.org/10.2139/ssrn.5907882openalex-snapshot

Privacy Meets Retrieval: The Performance Consequences of De-Identification in Retrieval-Augmented Generation

inferred← citeshttps://doi.org/10.2139/ssrn.6033215openalex-snapshot

A Survey of Large Language Models for Time Series Anomaly Detection: Methods, Challenges, and Future Directions

inferred← citeshttps://doi.org/10.3390/computers14090358openalex-snapshot

Privacy Threats and Privacy Preservation in Multiple Data Releases of High-Dimensional Datasets

inferred← citeshttps://doi.org/10.3390/electronics15071519openalex-snapshot

Trustworthy Intelligence: Split Learning–Embedded Large Language Models for Smart IoT Healthcare Systems

inferred← citeshttps://doi.org/10.3390/machines14030322openalex-snapshot

Research on Root Cause Analysis Method for Certain Civil Aircraft Based on Ensemble Learning and Large Language Model Reasoning

inferred← citeshttps://doi.org/10.36074/grail-of-science.01.05.2026.088openalex-snapshot

АНАЛІЗ КАНАЛІВ ВИТОКУ ДАНИХ ЧЕРЕЗ СЕРВІСИ НА ОСНОВІ ВЕЛИКИХ МОВНИХ МОДЕЛЕЙ

inferred← citeshttps://doi.org/10.5539/elt.v17n9p14openalex-snapshot

Prompt Engineering for Applied Linguistics: Elements, Examples, Techniques, and Strategies

Editorial review for independent work. ICSAC — the Institute for Complexity Science and Advanced Computing — runs a structured editorial panel for researchers publishing outside journals, and publishes on CiteStamp rails. Submission is free and goes through ORCID: icsacinstitute.org/submit.