ML Anthology

Geiping, Jonas

59 publications

ICML 2025 An Interpretable N-Gram Perplexity Threat Model for Large Language Model Jailbreaks Valentyn Boreiko, Alexander Panfilov, Vaclav Voracek, Matthias Hein, Jonas Geiping
ICLRW 2025 Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs Abhimanyu Hans, Yuxin Wen, Neel Jain, John Kirchenbauer, Hamid Kazemi, Prajwal Singhania, Siddharth Singh, Gowthami Somepalli, Jonas Geiping, Abhinav Bhatele, Tom Goldstein
ICLRW 2025 Can Language Models Falsify? the Need for Inverse Benchmarking Shiven Sinha, Shashwat Goel, Ponnurangam Kumaraguru, Jonas Geiping, Matthias Bethge, Ameya Prabhu
ICLRW 2025 Can You Finetune Your Binoculars? Embedding Text Watermarks into the Weights of Large Language Models Fay Elhassan, Niccolò Ajroldi, Antonio Orvieto, Jonas Geiping
ICML 2025 Great Models Think Alike and This Undermines AI Oversight Shashwat Goel, Joschka Strüber, Ilze Amanda Auzina, Karuna K Chandra, Ponnurangam Kumaraguru, Douwe Kiela, Ameya Prabhu, Matthias Bethge, Jonas Geiping
ICLRW 2025 Great Models Think Alike and This Undermines AI Oversight Shashwat Goel, Joschka Strüber, Ilze Amanda Auzina, Karuna K Chandra, Ponnurangam Kumaraguru, Douwe Kiela, Ameya Prabhu, Matthias Bethge, Jonas Geiping
NeurIPS 2025 Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach Jonas Geiping, Sean Michael McLeish, Neel Jain, John Kirchenbauer, Siddharth Singh, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Tom Goldstein
CVPRW 2025 Training Data Reconstruction: Privacy Due to Uncertainty? Christina Runkel, Kanchana Vaishnavi Gandikota, Jonas Geiping, Carola-Bibiane Schönlieb, Michael Moeller
ICML 2025 When, Where and Why to Average Weights? Niccolò Ajroldi, Antonio Orvieto, Jonas Geiping
NeurIPSW 2024 A Realistic Threat Model for Large Language Model Jailbreaks Valentyn Boreiko, Alexander Panfilov, Vaclav Voracek, Matthias Hein, Jonas Geiping
NeurIPS 2024 Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs Abhimanyu Hans, Yuxin Wen, Neel Jain, John Kirchenbauer, Hamid Kazemi, Prajwal Singhania, Siddharth Singh, Gowthami Somepalli, Jonas Geiping, Abhinav Bhatele, Tom Goldstein
NeurIPS 2024 CALVIN: Improved Contextual Video Captioning via Instruction Tuning Gowthami Somepalli, Arkabandhu Chowdhury, Ronen Basri, Jonas Geiping, Tom Goldstein, David Jacobs
ICLRW 2024 Coercing LLMs to Do and Reveal (almost) Anything Jonas Geiping, Alex Stein, Manli Shu, Khalid Saifullah, Yuxin Wen, Tom Goldstein
ICMLW 2024 Generating Potent Poisons and Backdoors from Scratch with Guided Diffusion Hossein Souri, Arpit Bansal, Hamid Kazemi, Liam H Fowl, Aniruddha Saha, Jonas Geiping, Andrew Gordon Wilson, Rama Chellappa, Tom Goldstein, Micah Goldblum
ICLR 2024 NEFTune: Noisy Embeddings Improve Instruction Finetuning 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
CVPR 2024 Object Recognition as Next Token Prediction Kaiyu Yue, Bor-Chun Chen, Jonas Geiping, Hengduo Li, Tom Goldstein, Ser-Nam Lim
ICLR 2024 On the Reliability of Watermarks for Large Language Models John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah, Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, Tom Goldstein
NeurIPS 2024 Privacy Backdoors: Enhancing Membership Inference Through Poisoning Pre-Trained Models Yuxin Wen, Leo Marchyok, Sanghyun Hong, Jonas Geiping, Tom Goldstein, Nicholas Carlini
ICML 2024 Spotting LLMs with Binoculars: Zero-Shot Detection of Machine-Generated Text Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, Hamid Kazemi, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
NeurIPS 2024 Transformers Can Do Arithmetic with the Right Embeddings Sean McLeish, Arpit Bansal, Alex Stein, Neel Jain, John Kirchenbauer, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Jonas Geiping, Avi Schwarzschild, Tom Goldstein
ICMLW 2024 Transformers Can Do Arithmetic with the Right Embeddings Sean Michael McLeish, Arpit Bansal, Alex Stein, Neel Jain, John Kirchenbauer, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Jonas Geiping, Avi Schwarzschild, Tom Goldstein
NeurIPSW 2024 Transformers Can Do Arithmetic with the Right Embeddings Sean Michael McLeish, Arpit Bansal, Alex Stein, Neel Jain, John Kirchenbauer, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Jonas Geiping, Avi Schwarzschild, Tom Goldstein
ICLR 2024 Universal Guidance for Diffusion Models Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Roni Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein
NeurIPSW 2024 What Do We Learn from Inverting CLIP Models? Hamid Kazemi, Atoosa Chegini, Jonas Geiping, Soheil Feizi, Tom Goldstein
NeurIPS 2023 A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning Valeriia Cherepanova, Roman Levin, Gowthami Somepalli, Jonas Geiping, C. Bayan Bruss, Andrew G Wilson, Tom Goldstein, Micah Goldblum
NeurIPSW 2023 A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning Valeriia Cherepanova, Roman Levin, Gowthami Somepalli, Jonas Geiping, C. Bruss, Andrew Wilson, Tom Goldstein, Micah Goldblum
TMLR 2023 A Survey on the Possibilities & Impossibilities of AI-Generated Text Detection Soumya Suvra Ghosal, Souradip Chakraborty, Jonas Geiping, Furong Huang, Dinesh Manocha, Amrit Bedi
ICML 2023 A Watermark for Large Language Models John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, Tom Goldstein
ICLR 2023 Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries Yuxin Wen, Arpit Bansal, Hamid Kazemi, Eitan Borgnia, Micah Goldblum, Jonas Geiping, Tom Goldstein
NeurIPS 2023 Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein
ICMLW 2023 Cramming: Training a Language Model on a Single GPU in One Day Jonas Geiping, Tom Goldstein
ICML 2023 Cramming: Training a Language Model on a Single GPU in One Day. Jonas Geiping, Tom Goldstein
ICLR 2023 Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models Liam H Fowl, Jonas Geiping, Steven Reich, Yuxin Wen, Wojciech Czaja, Micah Goldblum, Tom Goldstein
CVPR 2023 Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein
NeurIPS 2023 Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery Yuxin Wen, Neel Jain, John Kirchenbauer, Micah Goldblum, Jonas Geiping, Tom Goldstein
ICLR 2023 How Much Data Are Augmentations Worth? an Investigation into Scaling Laws, Invariance, and Implicit Regularization Jonas Geiping, Micah Goldblum, Gowthami Somepalli, Ravid Shwartz-Ziv, Tom Goldstein, Andrew Gordon Wilson
ICLR 2023 Loss Landscapes Are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent Ping-yeh Chiang, Renkun Ni, David Yu Miller, Arpit Bansal, Jonas Geiping, Micah Goldblum, Tom Goldstein
NeurIPS 2023 On the Exploitability of Instruction Tuning Manli Shu, Jiongxiao Wang, Chen Zhu, Jonas Geiping, Chaowei Xiao, Tom Goldstein
ICLR 2023 Panning for Gold in Federated Learning: Targeted Text Extraction Under Arbitrarily Large-Scale Aggregation Hong-Min Chu, Jonas Geiping, Liam H Fowl, Micah Goldblum, Tom Goldstein
NeurIPS 2023 Tree-Rings Watermarks: Invisible Fingerprints for Diffusion Images Yuxin Wen, John Kirchenbauer, Jonas Geiping, Tom Goldstein
ICMLW 2023 Understanding Data Replication in Diffusion Models Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein
NeurIPS 2023 Understanding and Mitigating Copying in Diffusion Models Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein
CVPRW 2023 Universal Guidance for Diffusion Models Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein
NeurIPS 2023 What Can We Learn from Unlearnable Datasets? Pedro Sandoval-Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein
NeurIPS 2022 Autoregressive Perturbations for Data Poisoning Pedro Sandoval-Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein, David Jacobs
NeurIPSW 2022 Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries Yuxin Wen, Arpit Bansal, Hamid Kazemi, Eitan Borgnia, Micah Goldblum, Jonas Geiping, Tom Goldstein
NeurIPSW 2022 DP-InstaHide: Data Augmentations Provably Enhance Guarantees Against Dataset Manipulations Eitan Borgnia, Jonas Geiping, Valeriia Cherepanova, Liam H Fowl, Arjun Gupta, Amin Ghiasi, Furong Huang, Micah Goldblum, Tom Goldstein
NeurIPSW 2022 Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models Liam H Fowl, Jonas Geiping, Steven Reich, Yuxin Wen, Wojciech Czaja, Micah Goldblum, Tom Goldstein
ICMLW 2022 How Much Data Is Augmentation Worth? Jonas Geiping, Gowthami Somepalli, Ravid Shwartz-Ziv, Andrew Gordon Wilson, Tom Goldstein, Micah Goldblum
NeurIPSW 2022 Panning for Gold in Federated Learning: Targeted Text Extraction Under Arbitrarily Large-Scale Aggregation Hong-Min Chu, Jonas Geiping, Liam H Fowl, Micah Goldblum, Tom Goldstein
CVPRW 2022 Poisons That Are Learned Faster Are More Effective Pedro Sandoval Segura, Vasu Singla, Liam Fowl, Jonas Geiping, Micah Goldblum, David Jacobs, Tom Goldstein
ICLR 2022 Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models Liam H Fowl, Jonas Geiping, Wojciech Czaja, Micah Goldblum, Tom Goldstein
ICLR 2022 Stochastic Training Is Not Necessary for Generalization Jonas Geiping, Micah Goldblum, Phil Pope, Michael Moeller, Tom Goldstein
NeurIPS 2021 Adversarial Examples Make Strong Poisons Liam Fowl, Micah Goldblum, Ping-yeh Chiang, Jonas Geiping, Wojciech Czaja, Tom Goldstein
NeurIPSW 2021 DARTS for Inverse Problems: A Study on Stability Jonas Geiping, Jovita Lukasik, Margret Keuper, Michael Moeller
ICLR 2021 Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching Jonas Geiping, Liam H Fowl, W. Ronny Huang, Wojciech Czaja, Gavin Taylor, Michael Moeller, Tom Goldstein
NeurIPS 2020 Inverting Gradients - How Easy Is It to Break Privacy in Federated Learning? Jonas Geiping, Hartmut Bauermeister, Hannah Dröge, Michael Moeller
NeurIPS 2020 MetaPoison: Practical General-Purpose Clean-Label Data Poisoning W. Ronny Huang, Jonas Geiping, Liam Fowl, Gavin Taylor, Tom Goldstein
ICLR 2020 Truth or Backpropaganda? an Empirical Investigation of Deep Learning Theory Micah Goldblum, Jonas Geiping, Avi Schwarzschild, Michael Moeller, Tom Goldstein