Jonas Geiping

Publication Activity (10 Years)

Years Active: 2016-2024
Publications (10 Years): 100

Top Venues

CoRR

ICLR

NeurIPS

ICASSP

Publications

Hamid Kazemi, Atoosa Malemir Chegini, Jonas Geiping, Soheil Feizi, Tom Goldstein
What do we learn from inverting CLIP models? CoRR (2024)
Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein
Universal Guidance for Diffusion Models. ICLR (2024)
Sean McLeish, Arpit Bansal, Alex Stein, Neel Jain, John Kirchenbauer, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Jonas Geiping, Avi Schwarzschild, Tom Goldstein
Transformers Can Do Arithmetic with the Right Embeddings. CoRR (2024)
Xiangyu Qi, Yangsibo Huang, Yi Zeng, Edoardo Debenedetti, Jonas Geiping, Luxi He, Kaixuan Huang, Udari Madhushani, Vikash Sehwag, Weijia Shi, Boyi Wei, Tinghao Xie, Danqi Chen, Pin-Yu Chen, Jeffrey Ding, Ruoxi Jia, Jiaqi Ma, Arvind Narayanan, Weijie J. Su, Mengdi Wang, Chaowei Xiao, Bo Li, Dawn Song, Peter Henderson, Prateek Mittal
AI Risk Management Should Incorporate Both Safety and Security. CoRR (2024)
John Kirchenbauer, Garrett Honke, Gowthami Somepalli, Jonas Geiping, Daphne Ippolito, Katherine Lee, Tom Goldstein, David Andre
LMD3: Language Model Data Density Dependence. CoRR (2024)
Hossein Souri, Arpit Bansal, Hamid Kazemi, Liam Fowl, Aniruddha Saha, Jonas Geiping, Andrew Gordon Wilson, Rama Chellappa, Tom Goldstein, Micah Goldblum
Generating Potent Poisons and Backdoors from Scratch with Guided Diffusion. CoRR (2024)
Jonas Geiping, Alex Stein, Manli Shu, Khalid Saifullah, Yuxin Wen, Tom Goldstein
Coercing LLMs to do and reveal (almost) anything. CoRR (2024)
Abhimanyu Hans, Yuxin Wen, Neel Jain, John Kirchenbauer, Hamid Kazemi, Prajwal Singhania, Siddharth Singh, Gowthami Somepalli, Jonas Geiping, Abhinav Bhatele, Tom Goldstein
Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs. CoRR (2024)
Yuxin Wen, Leo Marchyok, Sanghyun Hong, Jonas Geiping, Tom Goldstein, Nicholas Carlini
Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models. CoRR (2024)
Neel Jain, Ping-yeh Chiang, Yuxin Wen, John Kirchenbauer, Hong-Min Chu, Gowthami Somepalli, Brian R. Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
NEFTune: Noisy Embeddings Improve Instruction Finetuning. ICLR (2024)
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah, Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, Tom Goldstein
On the Reliability of Watermarks for Large Language Models. ICLR (2024)
Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, Hamid Kazemi, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text. CoRR (2024)
Gowthami Somepalli, Anubhav Gupta, Kamal Gupta, Shramay Palta, Micah Goldblum, Jonas Geiping, Abhinav Shrivastava, Tom Goldstein
Measuring Style Similarity in Diffusion Models. CoRR (2024)
Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein
Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models. CVPR (2023)
Jie S. Li, Yow-Ting Shiue, Yong-Siang Shih, Jonas Geiping
Augmenters at SemEval-2023 Task 1: Enhancing CLIP in Handling Compositionality and Ambiguity for Zero-Shot Visual WSD through Prompt Augmentation and Text-To-Image Diffusion. CoRR (2023)
Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein
Understanding and Mitigating Copying in Diffusion Models. CoRR (2023)
Jonas Geiping, Micah Goldblum, Gowthami Somepalli, Ravid Shwartz-Ziv, Tom Goldstein, Andrew Gordon Wilson
How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization. ICLR (2023)
Soumya Suvra Ghosal, Souradip Chakraborty, Jonas Geiping, Furong Huang, Dinesh Manocha, Amrit S. Bedi
A Survey on the Possibilities & Impossibilities of AI-generated Text Detection. Trans. Mach. Learn. Res. 2023 (2023)
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah, Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, Tom Goldstein
On the Reliability of Watermarks for Large Language Models. CoRR (2023)
Khalid Saifullah, Yuxin Wen, Jonas Geiping, Micah Goldblum, Tom Goldstein
Seeing in Words: Learning to Classify through Language Bottlenecks. Tiny Papers @ ICLR (2023)
Pedro Sandoval Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein
What Can We Learn from Unlearnable Datasets? CoRR (2023)
Kaiyu Yue, Bor-Chun Chen, Jonas Geiping, Hengduo Li, Tom Goldstein, Ser-Nam Lim
Object Recognition as Next Token Prediction. CoRR (2023)
Pedro Sandoval Segura, Jonas Geiping, Tom Goldstein
JPEG Compressed Images Can Bypass Protections Against AI Editing. CoRR (2023)
Yuxin Wen, John Kirchenbauer, Jonas Geiping, Tom Goldstein
Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust. CoRR (2023)
Yuxin Wen, Jonas Geiping, Micah Goldblum, Tom Goldstein
STYX: Adaptive Poisoning Attacks Against Byzantine-Robust Defenses in Federated Learning. ICASSP (2023)
Ping-yeh Chiang, Renkun Ni, David Yu Miller, Arpit Bansal, Jonas Geiping, Micah Goldblum, Tom Goldstein
Loss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent. ICLR (2023)
Jonas Geiping, Tom Goldstein
Cramming: Training a Language Model on a single GPU in one day. ICML (2023)
Valeriia Cherepanova, Roman Levin, Gowthami Somepalli, Jonas Geiping, C. Bayan Bruss, Andrew Gordon Wilson, Tom Goldstein, Micah Goldblum
A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning. CoRR (2023)
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, Tom Goldstein
A Watermark for Large Language Models. ICML (2023)
Yuxin Wen, Neel Jain, John Kirchenbauer, Micah Goldblum, Jonas Geiping, Tom Goldstein
Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery. CoRR (2023)
Khalid Saifullah, Yuxin Wen, Jonas Geiping, Micah Goldblum, Tom Goldstein
Seeing in Words: Learning to Classify through Language Bottlenecks. CoRR (2023)
Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein
Universal Guidance for Diffusion Models. CVPR Workshops (2023)
Randall Balestriero, Mark Ibrahim, Vlad Sobal, Ari Morcos, Shashank Shekhar, Tom Goldstein, Florian Bordes, Adrien Bardes, Grégoire Mialon, Yuandong Tian, Avi Schwarzschild, Andrew Gordon Wilson, Jonas Geiping, Quentin Garrido, Pierre Fernandez, Amir Bar, Hamed Pirsiavash, Yann LeCun, Micah Goldblum
A Cookbook of Self-Supervised Learning. CoRR (2023)
Hong-Min Chu, Jonas Geiping, Liam H. Fowl, Micah Goldblum, Tom Goldstein
Panning for Gold in Federated Learning: Targeted Text Extraction under Arbitrarily Large-Scale Aggregation. ICLR (2023)
Manli Shu, Jiongxiao Wang, Chen Zhu, Jonas Geiping, Chaowei Xiao, Tom Goldstein
On the Exploitability of Instruction Tuning. NeurIPS (2023)
Neel Jain, Avi Schwarzschild, Yuxin Wen, Gowthami Somepalli, John Kirchenbauer, Ping-yeh Chiang, Micah Goldblum, Aniruddha Saha, Jonas Geiping, Tom Goldstein
Baseline Defenses for Adversarial Attacks Against Aligned Language Models. CoRR (2023)
Manli Shu, Jiongxiao Wang, Chen Zhu, Jonas Geiping, Chaowei Xiao, Tom Goldstein
On the Exploitability of Instruction Tuning. CoRR (2023)
Yuxin Wen, John Kirchenbauer, Jonas Geiping, Tom Goldstein
Tree-Rings Watermarks: Invisible Fingerprints for Diffusion Images. NeurIPS (2023)
Yuxin Wen, Neel Jain, John Kirchenbauer, Micah Goldblum, Jonas Geiping, Tom Goldstein
Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery. NeurIPS (2023)
Valeriia Cherepanova, Roman Levin, Gowthami Somepalli, Jonas Geiping, C. Bayan Bruss, Andrew Gordon Wilson, Tom Goldstein, Micah Goldblum
A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning. NeurIPS (2023)
Pedro Sandoval Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein
What Can We Learn from Unlearnable Datasets? NeurIPS (2023)
Soumya Suvra Ghosal, Souradip Chakraborty, Jonas Geiping, Furong Huang, Dinesh Manocha, Amrit Singh Bedi
Towards Possibilities & Impossibilities of AI-generated Text Detection: A Survey. CoRR (2023)
Vasu Singla, Pedro Sandoval Segura, Micah Goldblum, Jonas Geiping, Tom Goldstein
A Simple and Efficient Baseline for Data Attribution on Images. CoRR (2023)
Jie Li, Yow-Ting Shiue, Yong-Siang Shih, Jonas Geiping
Augmenters at SemEval-2023 Task 1: Enhancing CLIP in Handling Compositionality and Ambiguity for Zero-Shot Visual WSD through Prompt Augmentation and Text-To-Image Diffusion. SemEval@ACL (2023)
Yuxin Wen, Arpit Bansal, Hamid Kazemi, Eitan Borgnia, Micah Goldblum, Jonas Geiping, Tom Goldstein
Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries. ICLR (2023)
John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, Tom Goldstein
A Watermark for Large Language Models. CoRR (2023)
Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein
Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise. NeurIPS (2023)
Liam H. Fowl, Jonas Geiping, Steven Reich, Yuxin Wen, Wojciech Czaja, Micah Goldblum, Tom Goldstein
Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models. ICLR (2023)
Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein
Universal Guidance for Diffusion Models. CoRR (2023)
Neel Jain, Khalid Saifullah, Yuxin Wen, John Kirchenbauer, Manli Shu, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
Bring Your Own Data! Self-Supervised Evaluation for Large Language Models. CoRR (2023)
Neel Jain, Ping-yeh Chiang, Yuxin Wen, John Kirchenbauer, Hong-Min Chu, Gowthami Somepalli, Brian R. Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
NEFTune: Noisy Embeddings Improve Instruction Finetuning. CoRR (2023)
Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein
Understanding and Mitigating Copying in Diffusion Models. NeurIPS (2023)
Jonas Geiping, Micah Goldblum, Phillip Pope, Michael Moeller, Tom Goldstein
Stochastic Training is Not Necessary for Generalization. ICLR (2022)
Yuxin Wen, Jonas Geiping, Liam Fowl, Micah Goldblum, Tom Goldstein
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification. CoRR (2022)
Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein
Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models. CoRR (2022)
Jonas Geiping, Tom Goldstein
Cramming: Training a Language Model on a Single GPU in One Day. CoRR (2022)
Kanchana Vaishnavi Gandikota, Jonas Geiping, Zorah Lähner, Adam Czaplinski, Michael Möller
A Simple Strategy to Provable Invariance via Orbit Mapping. ACCV (5) (2022)
Liam H. Fowl, Jonas Geiping, Wojciech Czaja, Micah Goldblum, Tom Goldstein
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models. ICLR (2022)
Yuxin Wen, Jonas Geiping, Liam Fowl, Hossein Souri, Rama Chellappa, Micah Goldblum, Tom Goldstein
Thinking Two Moves Ahead: Anticipating Other Users Improves Backdoor Attacks in Federated Learning. CoRR (2022)
Liam Fowl, Jonas Geiping, Steven Reich, Yuxin Wen, Wojtek Czaja, Micah Goldblum, Tom Goldstein
Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models. CoRR (2022)
Kanchana Vaishnavi Gandikota, Jonas Geiping, Zorah Lähner, Adam Czaplinski, Michael Möller
A Simple Strategy to Provable Invariance via Orbit Mapping. CoRR (2022)
Pedro Sandoval Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein, David Jacobs
Autoregressive Perturbations for Data Poisoning. NeurIPS (2022)
Pedro Sandoval Segura, Vasu Singla, Liam Fowl, Jonas Geiping, Micah Goldblum, David Jacobs, Tom Goldstein
Poisons that are learned faster are more effective. CVPR Workshops (2022)
Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie S. Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein
Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise. CoRR (2022)
Renkun Ni, Ping-yeh Chiang, Jonas Geiping, Micah Goldblum, Andrew Gordon Wilson, Tom Goldstein
K-SAM: Sharpness-Aware Minimization at the Speed of SGD. CoRR (2022)
Yuxin Wen, Arpit Bansal, Hamid Kazemi, Eitan Borgnia, Micah Goldblum, Jonas Geiping, Tom Goldstein
Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries. CoRR (2022)
Pedro Sandoval Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein, David W. Jacobs
Autoregressive Perturbations for Data Poisoning. CoRR (2022)
Jonas Geiping, Micah Goldblum, Gowthami Somepalli, Ravid Shwartz-Ziv, Tom Goldstein, Andrew Gordon Wilson
How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization. CoRR (2022)
Pedro Sandoval Segura, Vasu Singla, Liam Fowl, Jonas Geiping, Micah Goldblum, David Jacobs, Tom Goldstein
Poisons that are learned faster are more effective. CoRR (2022)
Yuxin Wen, Jonas Geiping, Liam Fowl, Micah Goldblum, Tom Goldstein
Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification. ICML (2022)
Liam Fowl, Jonas Geiping, Wojtek Czaja, Micah Goldblum, Tom Goldstein
Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models. CoRR (2021)
Jonas Geiping, Liam H. Fowl, W. Ronny Huang, Wojciech Czaja, Gavin Taylor, Michael Moeller, Tom Goldstein
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching. ICLR (2021)
Jonas Geiping, Micah Goldblum, Phillip E. Pope, Michael Moeller, Tom Goldstein
Stochastic Training is Not Necessary for Generalization. CoRR (2021)
Liam Fowl, Micah Goldblum, Ping-yeh Chiang, Jonas Geiping, Wojciech Czaja, Tom Goldstein
Adversarial Examples Make Strong Poisons. NeurIPS (2021)
Kanchana Vaishnavi Gandikota, Jonas Geiping, Zorah Lähner, Adam Czaplinski, Michael Möller
Training or Architecture? How to Incorporate Invariance in Neural Networks. CoRR (2021)
Jonas Geiping, Jovita Lukasik, Margret Keuper, Michael Moeller
DARTS for Inverse Problems: a Study on Hyperparameter Sensitivity. CoRR (2021)
Liam Fowl, Ping-Yeh Chiang, Micah Goldblum, Jonas Geiping, Arpit Bansal, Wojtek Czaja, Tom Goldstein
Preventing Unauthorized Use of Proprietary Data: Poisoning for Secure Dataset Release. CoRR (2021)
Liam Fowl, Micah Goldblum, Ping-Yeh Chiang, Jonas Geiping, Wojtek Czaja, Tom Goldstein
Adversarial Examples Make Strong Poisons. CoRR (2021)
Jonas Geiping, Liam Fowl, Gowthami Somepalli, Micah Goldblum, Michael Moeller, Tom Goldstein
What Doesn't Kill You Makes You Robust(er): Adversarial Training against Poisons and Backdoors. CoRR (2021)
Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta
Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff. ICASSP (2021)
Eitan Borgnia, Jonas Geiping, Valeriia Cherepanova, Liam Fowl, Arjun Gupta, Amin Ghiasi, Furong Huang, Micah Goldblum, Tom Goldstein
DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations. CoRR (2021)
Jonas Geiping, Fjedor Gaede, Hartmut Bauermeister, Michael Moeller
Fast Convex Relaxations using Graph Discretizations. CoRR (2020)
W. Ronny Huang, Jonas Geiping, Liam Fowl, Gavin Taylor, Tom Goldstein
MetaPoison: Practical General-purpose Clean-label Data Poisoning. CoRR (2020)
Micah Goldblum, Jonas Geiping, Avi Schwarzschild, Michael Moeller, Tom Goldstein
Truth or backpropaganda? An empirical investigation of deep learning theory. ICLR (2020)
Jonas Geiping, Hartmut Bauermeister, Hannah Dröge, Michael Moeller
Inverting Gradients - How easy is it to break privacy in federated learning? NeurIPS (2020)
Jonas Geiping, Hartmut Bauermeister, Hannah Dröge, Michael Moeller
Inverting Gradients - How easy is it to break privacy in federated learning? CoRR (2020)
Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Tom Goldstein, Renkun Ni, Steven Reich, Ali Shafahi
Witchcraft: Efficient PGD Attacks with Random Step Size. ICASSP (2020)
Jonas Geiping, Fjedor Gaede, Hartmut Bauermeister, Michael Moeller
Fast Convex Relaxations using Graph Discretizations. BMVC (2020)
Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta
Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff. CoRR (2020)
Jonas Geiping, Liam Fowl, W. Ronny Huang, Wojciech Czaja, Gavin Taylor, Michael Moeller, Tom Goldstein
Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching. CoRR (2020)
W. Ronny Huang, Jonas Geiping, Liam Fowl, Gavin Taylor, Tom Goldstein
MetaPoison: Practical General-purpose Clean-label Data Poisoning. NeurIPS (2020)
Micah Goldblum, Jonas Geiping, Avi Schwarzschild, Michael Moeller, Tom Goldstein
Truth or Backpropaganda? An Empirical Investigation of Deep Learning Theory. CoRR (2019)
Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Tom Goldstein, Renkun Ni, Steven Reich, Ali Shafahi
WITCHcraft: Efficient PGD attacks with random step size. CoRR (2019)
Jonas Geiping, Michael Moeller
Parametric Majorization for Data-Driven Energy Minimization Methods. CoRR (2019)
Jonas Geiping, Michael Moeller
Parametric Majorization for Data-Driven Energy Minimization Methods. ICCV (2019)
Andreas Görlitz, Jonas Geiping, Andreas Kolb
Piecewise Rigid Scene Flow with Implicit Motion Segmentation. IROS (2019)
Jonas Geiping, Michael Möller
Composite Optimization by Nonconvex Majorization-Minimization. CoRR (2018)
Jonas Geiping, Michael Möller
Composite Optimization by Nonconvex Majorization-Minimization. SIAM J. Imaging Sci. 11 (4) (2018)
Jonas Geiping, Hendrik Dirks, Daniel Cremers, Michael Möller
Multiframe Motion Coupling for Video Super Resolution. EMMCVPR (2017)
Hendrik Dirks, Jonas Geiping, Daniel Cremers, Michael Möller
Multiframe Motion Coupling via Infimal Convolution Regularization for Video Super Resolution. CoRR (2016)

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Publication Activity (10 Years)

Top Topics

Top Venues

Jonas Geiping