Adam Dziedzic

Orcid: 0000-0001-9786-2296

According to our database1, Adam Dziedzic authored at least 62 papers between 2016 and 2025.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Dataset
Other 

Links

On csauthors.net:

Bibliography

2025
Demystifying Foreground-Background Memorization in Diffusion Models.
CoRR, August, 2025

Adversarial Attacks and Defenses on Graph-aware Large Language Models (LLMs).
CoRR, August, 2025

Finding Dori: Memorization in Text-to-Image Diffusion Models Is Less Local Than Assumed.
CoRR, July, 2025

Implementing Adaptations for Vision AutoRegressive Model.
CoRR, July, 2025

Radioactive Watermarks in Diffusion and Autoregressive Image Generative Models.
CoRR, June, 2025

BitMark for Infinity: Watermarking Bitwise Autoregressive Image Generative Models.
CoRR, June, 2025

Efficient and Privacy-Preserving Soft Prompt Transfer for LLMs.
CoRR, June, 2025

Unlocking Post-hoc Dataset Inference with Synthetic Data.
CoRR, June, 2025

Strong Membership Inference Attacks on Massive Datasets and (Moderately) Large Language Models.
CoRR, May, 2025

Beautiful Images, Toxic Words: Understanding and Addressing Offensive Text in Generated Images.
CoRR, February, 2025

Privacy Attacks on Image AutoRegressive Models.
CoRR, February, 2025

MUC: Machine Unlearning for Contrastive Learning with Black-box Evaluation.
Trans. Mach. Learn. Res., 2025

Selective Prediction via Training Dynamics.
Trans. Mach. Learn. Res., 2025

Secure Noise Sampling for Differentially Private Collaborative Learning.
IACR Cryptol. ePrint Arch., 2025

Captured by Captions: On Memorization and its Mitigation in CLIP Models.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Precise Parameter Localization for Textual Generation in Diffusion Models.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

Differentially Private Federated Learning with Time-Adaptive Privacy Spending.
Proceedings of the Thirteenth International Conference on Learning Representations, 2025

CDI: Copyrighted Data Identification in Diffusion Models.
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2025

Differentially Private Prototypes for Imbalanced Transfer Learning.
Proceedings of the AAAI-25, Sponsored by the Association for the Advancement of Artificial Intelligence, February 25, 2025

2024
On the Privacy Risk of In-context Learning.
CoRR, 2024

Benchmarking Robust Self-Supervised Learning Across Diverse Downstream Tasks.
CoRR, 2024

Beyond the Mean: Differentially Private Prototypes for Private Transfer Learning.
CoRR, 2024

Alignment Calibration: Machine Unlearning for Contrastive Learning under Auditing.
CoRR, 2024

Decentralised, Collaborative, and Privacy-preserving Machine Learning for Multi-Hospital Data.
CoRR, 2024

Localizing Memorization in SSL Vision Encoders.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

LLM Dataset Inference: Did you train on my dataset?
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Finding NeMo: Localizing Neurons Responsible For Memorization in Diffusion Models.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Open LLMs are Necessary for Current Private Adaptations and Outperform their Closed Alternatives.
Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Memorization in Self-Supervised Learning Improves Downstream Generalization.
Proceedings of the Twelfth International Conference on Learning Representations, 2024

Efficient Model-Stealing Attacks Against Inductive Graph Neural Networks.
Proceedings of the ECAI 2024 - 27th European Conference on Artificial Intelligence, 19-24 October 2024, Santiago de Compostela, Spain, 2024

2023
Private Multi-Winner Voting for Machine Learning.
Proc. Priv. Enhancing Technol., January, 2023

Individualized PATE: Differentially Private Machine Learning with Individual Privacy Guarantees.
Proc. Priv. Enhancing Technol., January, 2023

Robust and Actively Secure Serverless Collaborative Learning.
CoRR, 2023

Is Federated Learning a Practical PET Yet?
CoRR, 2023

Robust and Actively Secure Serverless Collaborative Learning.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Bucks for Buckets (B4B): Active Defenses Against Stealing Encoders.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Flocks of Stochastic Parrots: Differentially Private Prompt Learning for Large Language Models.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Have it your way: Individualized Privacy Assignment for DP-SGD.
Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Reconstructing Individual Data Points in Federated Learning Hardened with Differential Privacy and Secure Aggregation.
Proceedings of the 8th IEEE European Symposium on Security and Privacy, 2023

When the Curious Abandon Honesty: Federated Learning Is Not Private.
Proceedings of the 8th IEEE European Symposium on Security and Privacy, 2023

2022
p-DkNN: Out-of-Distribution Detection Through Statistical Testing of Deep Representations.
CoRR, 2022

Selective Classification Via Neural Network Training Dynamics.
CoRR, 2022

Dataset Inference for Self-Supervised Models.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

On the Difficulty of Defending Self-Supervised Learning against Model Extraction.
Proceedings of the International Conference on Machine Learning, 2022

Increasing the Cost of Model Extraction with Calibrated Proof of Work.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
On the Exploitability of Audio Machine Learning Pipelines to Surreptitious Adversarial Examples.
CoRR, 2021

CaPC Learning: Confidential and Private Collaborative Learning.
Proceedings of the 9th International Conference on Learning Representations, 2021

2020
Machine Learning enabled Spectrum Sharing in Dense LTE-U/Wi-Fi Coexistence Scenarios.
CoRR, 2020

An Empirical Evaluation of Perturbation-based Defenses.
CoRR, 2020

Machine Learning based detection of multiple Wi-Fi BSSs for LTE-U CSAT.
Proceedings of the International Conference on Computing, Networking and Communications, 2020

Pretrained Transformers Improve Out-of-Distribution Robustness.
Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, 2020

2019
Artificial Intelligence in Resource-Constrained and Shared Environments.
ACM SIGOPS Oper. Syst. Rev., 2019

Band-limited Training and Inference for Convolutional Neural Networks.
Proceedings of the 36th International Conference on Machine Learning, 2019

DeepLens: Towards a Visual Data Management System.
Proceedings of the 9th Biennial Conference on Innovative Data Systems Research, 2019

2018
Columnstore and B+ tree - Are Hybrid Physical Designs Important?
Proceedings of the 2018 International Conference on Management of Data, 2018

2017
BigDAWG Polystore Release and Demonstration.
CoRR, 2017

Version 0.1 of the BigDAWG Polystore System.
CoRR, 2017

BigDAWG version 0.1.
Proceedings of the 2017 IEEE High Performance Extreme Computing Conference, 2017

Demonstrating the BigDAWG Polystore System for Ocean Metagenomics Analysis.
Proceedings of the 8th Biennial Conference on Innovative Data Systems Research, 2017

2016
DBMS Data Loading: An Analysis on Modern Hardware.
Proceedings of the Data Management on New Hardware, 2016

Integrating real-time and batch processing in a polystore.
Proceedings of the 2016 IEEE High Performance Extreme Computing Conference, 2016

Data transformation and migration in polystores.
Proceedings of the 2016 IEEE High Performance Extreme Computing Conference, 2016


  Loading...