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← Authors

Adam Dziedzic

26 papers · 2019–2026 · 6 conferences · across top CS/AI conferences

Achievements

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+13 more ↓ 🌍 Conference Polyglot (6) πŸƒ Academic Marathon (6) 🧭 Keyword Pioneer πŸŒ‰ Interdisciplinary Bridge 🐝 Cross-Pollinator (14)
🐝 Cross-Pollinator (14) 🌈 Renaissance Researcher (7) πŸ—ΊοΈ Taxonomy Completionist (39) πŸ”¬ Deep Specialist (10) 🀝 Dynamic Duo (16) πŸ‘‘ Triple Crown πŸ† Keyword Champion (2) πŸ† Grand Slam ⚑ Prolific Year (5) πŸ’Ž Century Club (23) πŸ”₯ Unstoppable (7) ❓ The Questioner πŸ—ƒοΈ Keyword Collector (81)

Conferences

NIPS (9) ICLR (6) ICML (5) AAAI (4) ACL (1) CVPR (1)

Top co-authors

Franziska Boenisch (19) Nicolas Papernot (9) Muhammad Ahmad Kaleem (5) Michael Backes (5) Jan DubiΕ„ski (4) Christopher A. Choquette-Choo (3) Wenhao Wang (3) Pratyush Maini (2) Tom Blanchard (2) Somesh Jha (2)

Research topics

Privacy (3) Differential Privacy (2)

Keywords

differential privacy (4) diffusion model (4) dataset inference (3) large language model (3) membership inference (3) self-supervised learning (3) transfer learning (2) adversarial attack (2) memorization localization (2) representation learning (2) model stealing (2) convolutional neural network (2) intellectual property (2) privacy-preserving learning (2) privacy-utility trade-off (2) model extraction (2) density estimation (1) natural language processing (1) image segmentation (1) embedding space (1)

Papers

Demystifying Foreground-Background Memorization in Diffusion Models AAAI 2026 On Stealing Graph Neural Network Models AAAI 2026 Beautiful Images, Toxic Words: Understanding and Addressing Offensive Text in Generated Images AAAI 2026 Privacy Attacks on Image AutoRegressive Models ICML 2025 Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs ICML 2025 Unlocking Post-hoc Dataset Inference with Synthetic Data ICML 2025 Differentially Private Prototypes for Imbalanced Transfer Learning AAAI 2025 CDI: Copyrighted Data Identification in Diffusion Models CVPR 2025 Captured by Captions: On Memorization and its Mitigation in CLIP Models ICLR 2025 Differentially Private Federated Learning with Time-Adaptive Privacy Spending ICLR 2025 Precise Parameter Localization for Textual Generation in Diffusion Models ICLR 2025 Open LLMs are Necessary for Current Private Adaptations and Outperform their Closed Alternatives NIPS 2024 Memorization in Self-Supervised Learning Improves Downstream Generalization ICLR 2024 Localizing Memorization in SSL Vision Encoders NIPS 2024 Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models NIPS 2024 LLM Dataset Inference: Did you train on my dataset? NIPS 2024 Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models NIPS 2023 Have it your way: Individualized Privacy Assignment for DP-SGD NIPS 2023 Robust and Actively Secure Serverless Collaborative Learning NIPS 2023 Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders NIPS 2023 Increasing the Cost of Model Extraction with Calibrated Proof of Work ICLR 2022 Dataset Inference for Self-Supervised Models NIPS 2022 On the Difficulty of Defending Self-Supervised Learning against Model Extraction ICML 2022 CaPC Learning: Confidential and Private Collaborative Learning ICLR 2021 Pretrained Transformers Improve Out-of-Distribution Robustness ACL 2020 Band-limited Training and Inference for Convolutional Neural Networks ICML 2019