Jonas Geiping - RankMe

145 papers A* 38A 3Misc 3Journal 90Unranked 10

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Claudini: Autoresearch Discovers State-of-the-Art Adversarial Attack Algorithms for LLMs. CoRR Alexander Panfilov, Peter Romov, Igor Shilov, Yves-Alexandre de Montjoye, Jonas Geiping, Maksym Andriushchenko
2026	A*	`conf`	MedSAMix: A Training-Free Model Merging Approach for Medical Image Segmentation. AAAI Yanwu Yang, Guinan Su, Jiesi Hu, Francesco Sammarco, Jonas Geiping, Thomas Wolfers
2026	J	`jnl`	NESSiE: The Necessary Safety Benchmark - Identifying Errors that should not Exist. CoRR Johannes Bertram, Jonas Geiping
2025	J	`jnl`	Adaptive Attacks on Trusted Monitors Subvert AI Control Protocols. CoRR Mikhail Terekhov, Alexander Panfilov, Daniil Dzenhaliou, Caglar Gulcehre, Maksym Andriushchenko, Ameya Prabhu, Jonas Geiping
2025	A*	`conf`	An Interpretable N-gram Perplexity Threat Model for Large Language Model Jailbreaks. ICML Valentyn Boreiko, Alexander Panfilov, Václav Vorácek, Matthias Hein, Jonas Geiping
2025	J	`jnl`	Answer Matching Outperforms Multiple Choice for Language Model Evaluation. CoRR Nikhil Chandak, Shashwat Goel, Ameya Prabhu, Moritz Hardt, Jonas Geiping
2025	J	`jnl`	Can Language Models Falsify? Evaluating Algorithmic Reasoning with Counterexample Creation. CoRR Shiven Sinha, Shashwat Goel, Ponnurangam Kumaraguru, Jonas Geiping, Matthias Bethge, Ameya Prabhu
2025	J	`jnl`	Can you Finetune your Binoculars? Embedding Text Watermarks into the Weights of Large Language Models. CoRR Fay Elhassan, Niccolò Ajroldi, Antonio Orvieto, Jonas Geiping
2025	J	`jnl`	Capability-Based Scaling Laws for LLM Red-Teaming. CoRR Alexander Panfilov, Paul Kassianik, Maksym Andriushchenko, Jonas Geiping
2025	J	`jnl`	Democratizing AI: Open-source Scalable LLM Training on GPU-based Supercomputers. CoRR Siddharth Singh, Prajwal Singhania, Aditya K. Ranjan, John Kirchenbauer, Jonas Geiping, Yuxin Wen, Neel Jain, Abhimanyu Hans, Manli Shu, Aditya Tomar, Tom Goldstein, Abhinav Bhatele
2025	J	`jnl`	Efficient Parallel Samplers for Recurrent-Depth Models and Their Connection to Diffusion Language Models. CoRR Jonas Geiping, Xinyu Yang, Guinan Su
2025	J	`jnl`	Fine, I'll Merge It Myself: A Multi-Fidelity Framework for Automated Model Merging. CoRR Guinan Su, Jonas Geiping
2025	J	`jnl`	GPTailor: Large Language Model Pruning Through Layer Cutting and Stitching. CoRR Guinan Su, Li Shen, Lu Yin, Shiwei Liu, Yanwu Yang, Jonas Geiping
2025	A*	`conf`	Great Models Think Alike and this Undermines AI Oversight. ICML Shashwat Goel, Joschka Strüber, Ilze Amanda Auzina, Karuna K. Chandra, Ponnurangam Kumaraguru, Douwe Kiela, Ameya Prabhu, Matthias Bethge, Jonas Geiping
2025	J	`jnl`	Great Models Think Alike and this Undermines AI Oversight. CoRR Shashwat Goel, Joschka Strüber, Ilze Amanda Auzina, Karuna K. Chandra, Ponnurangam Kumaraguru, Douwe Kiela, Ameya Prabhu, Matthias Bethge, Jonas Geiping
2025	J	`jnl`	Is your batch size the problem? Revisiting the Adam-SGD gap in language modeling. CoRR Teodora Sreckovic, Jonas Geiping, Antonio Orvieto
2025	—	`conf`	LLM-Generated Passphrases That Are Secure and Easy to Remember. NAACL (Findings) Jie S. Li, Jonas Geiping, Micah Goldblum, Aniruddha Saha, Tom Goldstein
2025	J	`jnl`	MedSAMix: A Training-Free Model Merging Approach for Medical Image Segmentation. CoRR Yanwu Yang, Guinan Su, Jiesi Hu, Francesco Sammarco, Jonas Geiping, Thomas Wolfers
2025	J	`jnl`	Pitfalls in Evaluating Language Model Forecasters. CoRR Daniel Paleka, Shashwat Goel, Jonas Geiping, Florian Tramèr
2025	J	`jnl`	Rewiring Experts on the Fly:Continuous Rerouting for Better Online Adaptation in Mixture-of-Expert models. CoRR Guinan Su, Yanwu Yang, Li Shen, Lu Yin, Shiwei Liu, Jonas Geiping
2025	J	`jnl`	Sample Smart, Not Hard: Correctness-First Decoding for Better Reasoning in LLMs. CoRR Xueyan Li, Guinan Su, Mrinmaya Sachan, Jonas Geiping
2025	J	`jnl`	Scaling Open-Ended Reasoning to Predict the Future. CoRR Nikhil Chandak, Shashwat Goel, Ameya Prabhu, Moritz Hardt, Jonas Geiping
2025	J	`jnl`	Scaling up Test-Time Compute with Latent Reasoning: A Recurrent Depth Approach. CoRR Jonas Geiping, Sean McLeish, Neel Jain, John Kirchenbauer, Siddharth Singh, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Tom Goldstein
2025	J	`jnl`	Strategic Dishonesty Can Undermine AI Safety Evaluations of Frontier LLMs. CoRR Alexander Panfilov, Evgenii Kortukov, Kristina Nikolic, Matthias Bethge, Sebastian Lapuschkin, Wojciech Samek, Ameya Prabhu, Maksym Andriushchenko, Jonas Geiping
2025	J	`jnl`	Teaching Pretrained Language Models to Think Deeper with Retrofitted Recurrence. CoRR Sean McLeish, Ang Li, John Kirchenbauer, Dayal Singh Kalra, Brian R. Bartoldson, Bhavya Kailkhura, Avi Schwarzschild, Jonas Geiping, Tom Goldstein, Micah Goldblum
2025	J	`jnl`	The Illusion of Diminishing Returns: Measuring Long Horizon Execution in LLMs. CoRR Akshit Sinha, Arvindh Arun, Shashwat Goel, Steffen Staab, Jonas Geiping
2025	J	`jnl`	Training AI Co-Scientists Using Rubric Rewards. CoRR Shashwat Goel, Rishi Hazra, Dulhan Jayalath, Timon Willi, Parag Jain, William F. Shen, Ilias Leontiadis, Francesco Barbieri, Yoram Bachrach, Jonas Geiping, Chenxi Whitehouse
2025	—	`conf`	Training Data Reconstruction: Privacy due to Uncertainty? CVPR Workshops Christina Runkel, Kanchana Vaishnavi Gandikota, Jonas Geiping, Carola-Bibiane Schönlieb, Michael Moeller
2025	J	`jnl`	Training Dynamics Impact Post-Training Quantization Robustness. CoRR Albert Catalan-Tatjer, Niccolò Ajroldi, Jonas Geiping
2025	J	`jnl`	When Fewer Layers Break More Chains: Layer Pruning Harms Test-Time Scaling in LLMs. CoRR Keyu Wang, Tian Lyu, Guinan Su, Jonas Geiping, Lu Yin, Marco Canini, Shiwei Liu
2025	A*	`conf`	When, Where and Why to Average Weights? ICML Niccolò Ajroldi, Antonio Orvieto, Jonas Geiping
2025	J	`jnl`	When, Where and Why to Average Weights? CoRR Niccolò Ajroldi, Antonio Orvieto, Jonas Geiping
2024	J	`jnl`	A Realistic Threat Model for Large Language Model Jailbreaks. CoRR Valentyn Boreiko, Alexander Panfilov, Václav Vorácek, Matthias Hein, Jonas Geiping
2024	J	`jnl`	AI Risk Management Should Incorporate Both Safety and Security. CoRR 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
2024	A*	`conf`	Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs. NeurIPS Abhimanyu Hans, John Kirchenbauer, Yuxin Wen, Neel Jain, Hamid Kazemi, Prajwal Singhania, Siddharth Singh, Gowthami Somepalli, Jonas Geiping, Abhinav Bhatele, Tom Goldstein
2024	J	`jnl`	Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs. CoRR Abhimanyu Hans, Yuxin Wen, Neel Jain, John Kirchenbauer, Hamid Kazemi, Prajwal Singhania, Siddharth Singh, Gowthami Somepalli, Jonas Geiping, Abhinav Bhatele, Tom Goldstein
2024	A*	`conf`	CALVIN: Improved Contextual Video Captioning via Instruction Tuning. NeurIPS Gowthami Somepalli, Arkabandhu Chowdhury, Jonas Geiping, Ronen Basri, Tom Goldstein, David Jacobs
2024	J	`jnl`	Coercing LLMs to do and reveal (almost) anything. CoRR Jonas Geiping, Alex Stein, Manli Shu, Khalid Saifullah, Yuxin Wen, Tom Goldstein
2024	A	`conf`	Democratizing AI: Open-source Scalable LLM Training on GPU-based Supercomputers. SC Siddharth Singh, Prajwal Singhania, Aditya K. Ranjan, John Kirchenbauer, Jonas Geiping, Yuxin Wen, Neel Jain, Abhimanyu Hans, Manli Shu, Aditya Tomar, Tom Goldstein, Abhinav Bhatele
2024	—	`conf`	Efficiently Dispatching Flash Attention For Partially Filled Attention Masks. ENLSP Agniv Sharma, Jonas Geiping
2024	J	`jnl`	Efficiently Dispatching Flash Attention For Partially Filled Attention Masks. CoRR Agniv Sharma, Jonas Geiping
2024	J	`jnl`	Generating Potent Poisons and Backdoors from Scratch with Guided Diffusion. CoRR Hossein Souri, Arpit Bansal, Hamid Kazemi, Liam Fowl, Aniruddha Saha, Jonas Geiping, Andrew Gordon Wilson, Rama Chellappa, Tom Goldstein, Micah Goldblum
2024	—	`conf`	Investigating Style Similarity in Diffusion Models. ECCV (66) Gowthami Somepalli, Anubhav Gupta, Kamal Gupta, Shramay Palta, Micah Goldblum, Jonas Geiping, Abhinav Shrivastava, Tom Goldstein
2024	J	`jnl`	LMD3: Language Model Data Density Dependence. CoRR John Kirchenbauer, Garrett Honke, Gowthami Somepalli, Jonas Geiping, Daphne Ippolito, Katherine Lee, Tom Goldstein, David Andre
2024	J	`jnl`	Measuring Style Similarity in Diffusion Models. CoRR Gowthami Somepalli, Anubhav Gupta, Kamal Gupta, Shramay Palta, Micah Goldblum, Jonas Geiping, Abhinav Shrivastava, Tom Goldstein
2024	A*	`conf`	NEFTune: Noisy Embeddings Improve Instruction Finetuning. ICLR 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
2024	A*	`conf`	Object Recognition as Next Token Prediction. CVPR Kaiyu Yue, Bor-Chun Chen, Jonas Geiping, Hengduo Li, Tom Goldstein, Ser-Nam Lim
2024	A*	`conf`	On the Reliability of Watermarks for Large Language Models. ICLR John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah, Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, Tom Goldstein
2024	A*	`conf`	Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models. NeurIPS Yuxin Wen, Leo Marchyok, Sanghyun Hong, Jonas Geiping, Tom Goldstein, Nicholas Carlini
2024	J	`jnl`	Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models. CoRR Yuxin Wen, Leo Marchyok, Sanghyun Hong, Jonas Geiping, Tom Goldstein, Nicholas Carlini
2024	A*	`conf`	Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text. ICML Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, Hamid Kazemi, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
2024	J	`jnl`	Spotting LLMs With Binoculars: Zero-Shot Detection of Machine-Generated Text. CoRR Abhimanyu Hans, Avi Schwarzschild, Valeriia Cherepanova, Hamid Kazemi, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
2024	J	`jnl`	Training Data Reconstruction: Privacy due to Uncertainty? CoRR Christina Runkel, Kanchana Vaishnavi Gandikota, Jonas Geiping, Carola-Bibiane Schönlieb, Michael Moeller
2024	A*	`conf`	Transformers Can Do Arithmetic with the Right Embeddings. NeurIPS Sean McLeish, Arpit Bansal, Alex Stein, Neel Jain, John Kirchenbauer, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Jonas Geiping, Avi Schwarzschild, Tom Goldstein
2024	J	`jnl`	Transformers Can Do Arithmetic with the Right Embeddings. CoRR Sean McLeish, Arpit Bansal, Alex Stein, Neel Jain, John Kirchenbauer, Brian R. Bartoldson, Bhavya Kailkhura, Abhinav Bhatele, Jonas Geiping, Avi Schwarzschild, Tom Goldstein
2024	A*	`conf`	Universal Guidance for Diffusion Models. ICLR Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein
2024	J	`jnl`	What do we learn from inverting CLIP models? CoRR Hamid Kazemi, Atoosa Malemir Chegini, Jonas Geiping, Soheil Feizi, Tom Goldstein
2023	J	`jnl`	A Cookbook of Self-Supervised Learning. CoRR 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
2023	A*	`conf`	A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning. NeurIPS Valeriia Cherepanova, Roman Levin, Gowthami Somepalli, Jonas Geiping, C. Bayan Bruss, Andrew Gordon Wilson, Tom Goldstein, Micah Goldblum
2023	J	`jnl`	A Performance-Driven Benchmark for Feature Selection in Tabular Deep Learning. CoRR Valeriia Cherepanova, Roman Levin, Gowthami Somepalli, Jonas Geiping, C. Bayan Bruss, Andrew Gordon Wilson, Tom Goldstein, Micah Goldblum
2023	J	`jnl`	A Simple and Efficient Baseline for Data Attribution on Images. CoRR Vasu Singla, Pedro Sandoval Segura, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	J	`jnl`	A Survey on the Possibilities & Impossibilities of AI-generated Text Detection. Trans. Mach. Learn. Res. Soumya Suvra Ghosal, Souradip Chakraborty, Jonas Geiping, Furong Huang, Dinesh Manocha, Amrit S. Bedi
2023	A*	`conf`	A Watermark for Large Language Models. ICML John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, Tom Goldstein
2023	J	`jnl`	A Watermark for Large Language Models. CoRR John Kirchenbauer, Jonas Geiping, Yuxin Wen, Jonathan Katz, Ian Miers, Tom Goldstein
2023	—	`conf`	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 Jie S. Li, Yow-Ting Shiue, Yong-Siang Shih, Jonas Geiping
2023	J	`jnl`	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 Jie S. Li, Yow-Ting Shiue, Yong-Siang Shih, Jonas Geiping
2023	J	`jnl`	Baseline Defenses for Adversarial Attacks Against Aligned Language Models. CoRR Neel Jain, Avi Schwarzschild, Yuxin Wen, Gowthami Somepalli, John Kirchenbauer, Ping-Yeh Chiang, Micah Goldblum, Aniruddha Saha, Jonas Geiping, Tom Goldstein
2023	J	`jnl`	Bring Your Own Data! Self-Supervised Evaluation for Large Language Models. CoRR Neel Jain, Khalid Saifullah, Yuxin Wen, John Kirchenbauer, Manli Shu, Aniruddha Saha, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	A*	`conf`	Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries. ICLR Yuxin Wen, Arpit Bansal, Hamid Kazemi, Eitan Borgnia, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	A*	`conf`	Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise. NeurIPS Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	A*	`conf`	Cramming: Training a Language Model on a single GPU in one day. ICML Jonas Geiping, Tom Goldstein
2023	A*	`conf`	Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models. ICLR Liam H. Fowl, Jonas Geiping, Steven Reich, Yuxin Wen, Wojciech Czaja, Micah Goldblum, Tom Goldstein
2023	A*	`conf`	Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models. CVPR Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	A*	`conf`	Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery. NeurIPS Yuxin Wen, Neel Jain, John Kirchenbauer, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	J	`jnl`	Hard Prompts Made Easy: Gradient-Based Discrete Optimization for Prompt Tuning and Discovery. CoRR Yuxin Wen, Neel Jain, John Kirchenbauer, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	A*	`conf`	How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization. ICLR Jonas Geiping, Micah Goldblum, Gowthami Somepalli, Ravid Shwartz-Ziv, Tom Goldstein, Andrew Gordon Wilson
2023	J	`jnl`	JPEG Compressed Images Can Bypass Protections Against AI Editing. CoRR Pedro Sandoval Segura, Jonas Geiping, Tom Goldstein
2023	A*	`conf`	Loss Landscapes are All You Need: Neural Network Generalization Can Be Explained Without the Implicit Bias of Gradient Descent. ICLR Ping-Yeh Chiang, Renkun Ni, David Yu Miller, Arpit Bansal, Jonas Geiping, Micah Goldblum, Tom Goldstein
2023	J	`jnl`	NEFTune: Noisy Embeddings Improve Instruction Finetuning. CoRR 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
2023	J	`jnl`	Object Recognition as Next Token Prediction. CoRR Kaiyu Yue, Bor-Chun Chen, Jonas Geiping, Hengduo Li, Tom Goldstein, Ser-Nam Lim
2023	A*	`conf`	On the Exploitability of Instruction Tuning. NeurIPS Manli Shu, Jiongxiao Wang, Chen Zhu, Jonas Geiping, Chaowei Xiao, Tom Goldstein
2023	J	`jnl`	On the Exploitability of Instruction Tuning. CoRR Manli Shu, Jiongxiao Wang, Chen Zhu, Jonas Geiping, Chaowei Xiao, Tom Goldstein
2023	J	`jnl`	On the Reliability of Watermarks for Large Language Models. CoRR John Kirchenbauer, Jonas Geiping, Yuxin Wen, Manli Shu, Khalid Saifullah, Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, Tom Goldstein
2023	A*	`conf`	Panning for Gold in Federated Learning: Targeted Text Extraction under Arbitrarily Large-Scale Aggregation. ICLR Hong-Min Chu, Jonas Geiping, Liam H. Fowl, Micah Goldblum, Tom Goldstein
2023	Misc	`conf`	STYX: Adaptive Poisoning Attacks Against Byzantine-Robust Defenses in Federated Learning. ICASSP Yuxin Wen, Jonas Geiping, Micah Goldblum, Tom Goldstein
2023	—	`conf`	Seeing in Words: Learning to Classify through Language Bottlenecks. Tiny Papers @ ICLR Khalid Saifullah, Yuxin Wen, Jonas Geiping, Micah Goldblum, Tom Goldstein
2023	J	`jnl`	Seeing in Words: Learning to Classify through Language Bottlenecks. CoRR Khalid Saifullah, Yuxin Wen, Jonas Geiping, Micah Goldblum, Tom Goldstein
2023	J	`jnl`	Towards Possibilities & Impossibilities of AI-generated Text Detection: A Survey. CoRR Soumya Suvra Ghosal, Souradip Chakraborty, Jonas Geiping, Furong Huang, Dinesh Manocha, Amrit Singh Bedi
2023	J	`jnl`	Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust. CoRR Yuxin Wen, John Kirchenbauer, Jonas Geiping, Tom Goldstein
2023	A*	`conf`	Tree-Rings Watermarks: Invisible Fingerprints for Diffusion Images. NeurIPS Yuxin Wen, John Kirchenbauer, Jonas Geiping, Tom Goldstein
2023	A*	`conf`	Understanding and Mitigating Copying in Diffusion Models. NeurIPS Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	J	`jnl`	Understanding and Mitigating Copying in Diffusion Models. CoRR Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	—	`conf`	Universal Guidance for Diffusion Models. CVPR Workshops Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	J	`jnl`	Universal Guidance for Diffusion Models. CoRR Arpit Bansal, Hong-Min Chu, Avi Schwarzschild, Soumyadip Sengupta, Micah Goldblum, Jonas Geiping, Tom Goldstein
2023	A*	`conf`	What Can We Learn from Unlearnable Datasets? NeurIPS Pedro Sandoval Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein
2023	J	`jnl`	What Can We Learn from Unlearnable Datasets? CoRR Pedro Sandoval Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein
2022	—	`conf`	A Simple Strategy to Provable Invariance via Orbit Mapping. ACCV (5) Kanchana Vaishnavi Gandikota, Jonas Geiping, Zorah Lähner, Adam Czaplinski, Michael Möller
2022	J	`jnl`	A Simple Strategy to Provable Invariance via Orbit Mapping. CoRR Kanchana Vaishnavi Gandikota, Jonas Geiping, Zorah Lähner, Adam Czaplinski, Michael Möller
2022	A*	`conf`	Autoregressive Perturbations for Data Poisoning. NeurIPS Pedro Sandoval Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein, David Jacobs
2022	J	`jnl`	Autoregressive Perturbations for Data Poisoning. CoRR Pedro Sandoval Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein, David W. Jacobs
2022	J	`jnl`	Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries. CoRR Yuxin Wen, Arpit Bansal, Hamid Kazemi, Eitan Borgnia, Micah Goldblum, Jonas Geiping, Tom Goldstein
2022	J	`jnl`	Cold Diffusion: Inverting Arbitrary Image Transforms Without Noise. CoRR Arpit Bansal, Eitan Borgnia, Hong-Min Chu, Jie S. Li, Hamid Kazemi, Furong Huang, Micah Goldblum, Jonas Geiping, Tom Goldstein
2022	J	`jnl`	Cramming: Training a Language Model on a Single GPU in One Day. CoRR Jonas Geiping, Tom Goldstein
2022	J	`jnl`	Decepticons: Corrupted Transformers Breach Privacy in Federated Learning for Language Models. CoRR Liam Fowl, Jonas Geiping, Steven Reich, Yuxin Wen, Wojtek Czaja, Micah Goldblum, Tom Goldstein
2022	J	`jnl`	Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models. CoRR Gowthami Somepalli, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein
2022	A*	`conf`	Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification. ICML Yuxin Wen, Jonas Geiping, Liam Fowl, Micah Goldblum, Tom Goldstein
2022	J	`jnl`	Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification. CoRR Yuxin Wen, Jonas Geiping, Liam Fowl, Micah Goldblum, Tom Goldstein
2022	J	`jnl`	How Much Data Are Augmentations Worth? An Investigation into Scaling Laws, Invariance, and Implicit Regularization. CoRR Jonas Geiping, Micah Goldblum, Gowthami Somepalli, Ravid Shwartz-Ziv, Tom Goldstein, Andrew Gordon Wilson
2022	J	`jnl`	K-SAM: Sharpness-Aware Minimization at the Speed of SGD. CoRR Renkun Ni, Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Andrew Gordon Wilson, Tom Goldstein
2022	—	`conf`	Poisons that are learned faster are more effective. CVPR Workshops Pedro Sandoval Segura, Vasu Singla, Liam Fowl, Jonas Geiping, Micah Goldblum, David Jacobs, Tom Goldstein
2022	J	`jnl`	Poisons that are learned faster are more effective. CoRR Pedro Sandoval Segura, Vasu Singla, Liam Fowl, Jonas Geiping, Micah Goldblum, David Jacobs, Tom Goldstein
2022	A*	`conf`	Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models. ICLR Liam H. Fowl, Jonas Geiping, Wojciech Czaja, Micah Goldblum, Tom Goldstein
2022	A*	`conf`	Stochastic Training is Not Necessary for Generalization. ICLR Jonas Geiping, Micah Goldblum, Phillip Pope, Michael Moeller, Tom Goldstein
2022	J	`jnl`	Thinking Two Moves Ahead: Anticipating Other Users Improves Backdoor Attacks in Federated Learning. CoRR Yuxin Wen, Jonas Geiping, Liam Fowl, Hossein Souri, Rama Chellappa, Micah Goldblum, Tom Goldstein
2021	A*	`conf`	Adversarial Examples Make Strong Poisons. NeurIPS Liam Fowl, Micah Goldblum, Ping-Yeh Chiang, Jonas Geiping, Wojciech Czaja, Tom Goldstein
2021	J	`jnl`	Adversarial Examples Make Strong Poisons. CoRR Liam Fowl, Micah Goldblum, Ping-Yeh Chiang, Jonas Geiping, Wojtek Czaja, Tom Goldstein
2021	J	`jnl`	DARTS for Inverse Problems: a Study on Hyperparameter Sensitivity. CoRR Jonas Geiping, Jovita Lukasik, Margret Keuper, Michael Moeller
2021	J	`jnl`	DP-InstaHide: Provably Defusing Poisoning and Backdoor Attacks with Differentially Private Data Augmentations. CoRR Eitan Borgnia, Jonas Geiping, Valeriia Cherepanova, Liam Fowl, Arjun Gupta, Amin Ghiasi, Furong Huang, Micah Goldblum, Tom Goldstein
2021	—	`—`	Modern optimization techniques in computer vision: from variational models to machine learning security. Jonas Geiping
2021	J	`jnl`	Preventing Unauthorized Use of Proprietary Data: Poisoning for Secure Dataset Release. CoRR Liam Fowl, Ping-Yeh Chiang, Micah Goldblum, Jonas Geiping, Arpit Bansal, Wojtek Czaja, Tom Goldstein
2021	J	`jnl`	Robbing the Fed: Directly Obtaining Private Data in Federated Learning with Modified Models. CoRR Liam Fowl, Jonas Geiping, Wojtek Czaja, Micah Goldblum, Tom Goldstein
2021	J	`jnl`	Stochastic Training is Not Necessary for Generalization. CoRR Jonas Geiping, Micah Goldblum, Phillip E. Pope, Michael Moeller, Tom Goldstein
2021	Misc	`conf`	Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff. ICASSP Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta
2021	J	`jnl`	Training or Architecture? How to Incorporate Invariance in Neural Networks. CoRR Kanchana Vaishnavi Gandikota, Jonas Geiping, Zorah Lähner, Adam Czaplinski, Michael Möller
2021	J	`jnl`	What Doesn't Kill You Makes You Robust(er): Adversarial Training against Poisons and Backdoors. CoRR Jonas Geiping, Liam Fowl, Gowthami Somepalli, Micah Goldblum, Michael Moeller, Tom Goldstein
2021	A*	`conf`	Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching. ICLR Jonas Geiping, Liam H. Fowl, W. Ronny Huang, Wojciech Czaja, Gavin Taylor, Michael Moeller, Tom Goldstein
2020	A	`conf`	Fast Convex Relaxations using Graph Discretizations. BMVC Jonas Geiping, Fjedor Gaede, Hartmut Bauermeister, Michael Moeller
2020	J	`jnl`	Fast Convex Relaxations using Graph Discretizations. CoRR Jonas Geiping, Fjedor Gaede, Hartmut Bauermeister, Michael Moeller
2020	A*	`conf`	Inverting Gradients - How easy is it to break privacy in federated learning? NeurIPS Jonas Geiping, Hartmut Bauermeister, Hannah Dröge, Michael Moeller
2020	J	`jnl`	Inverting Gradients - How easy is it to break privacy in federated learning? CoRR Jonas Geiping, Hartmut Bauermeister, Hannah Dröge, Michael Moeller
2020	A*	`conf`	MetaPoison: Practical General-purpose Clean-label Data Poisoning. NeurIPS W. Ronny Huang, Jonas Geiping, Liam Fowl, Gavin Taylor, Tom Goldstein
2020	J	`jnl`	MetaPoison: Practical General-purpose Clean-label Data Poisoning. CoRR W. Ronny Huang, Jonas Geiping, Liam Fowl, Gavin Taylor, Tom Goldstein
2020	J	`jnl`	Strong Data Augmentation Sanitizes Poisoning and Backdoor Attacks Without an Accuracy Tradeoff. CoRR Eitan Borgnia, Valeriia Cherepanova, Liam Fowl, Amin Ghiasi, Jonas Geiping, Micah Goldblum, Tom Goldstein, Arjun Gupta
2020	A*	`conf`	Truth or backpropaganda? An empirical investigation of deep learning theory. ICLR Micah Goldblum, Jonas Geiping, Avi Schwarzschild, Michael Moeller, Tom Goldstein
2020	Misc	`conf`	Witchcraft: Efficient PGD Attacks with Random Step Size. ICASSP Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Tom Goldstein, Renkun Ni, Steven Reich, Ali Shafahi
2020	J	`jnl`	Witches' Brew: Industrial Scale Data Poisoning via Gradient Matching. CoRR Jonas Geiping, Liam Fowl, W. Ronny Huang, Wojciech Czaja, Gavin Taylor, Michael Moeller, Tom Goldstein
2019	A*	`conf`	Parametric Majorization for Data-Driven Energy Minimization Methods. ICCV Jonas Geiping, Michael Moeller
2019	J	`jnl`	Parametric Majorization for Data-Driven Energy Minimization Methods. CoRR Jonas Geiping, Michael Moeller
2019	A	`conf`	Piecewise Rigid Scene Flow with Implicit Motion Segmentation. IROS Andreas Görlitz, Jonas Geiping, Andreas Kolb
2019	J	`jnl`	Truth or Backpropaganda? An Empirical Investigation of Deep Learning Theory. CoRR Micah Goldblum, Jonas Geiping, Avi Schwarzschild, Michael Moeller, Tom Goldstein
2019	J	`jnl`	WITCHcraft: Efficient PGD attacks with random step size. CoRR Ping-Yeh Chiang, Jonas Geiping, Micah Goldblum, Tom Goldstein, Renkun Ni, Steven Reich, Ali Shafahi
2018	J	`jnl`	Composite Optimization by Nonconvex Majorization-Minimization. CoRR Jonas Geiping, Michael Möller
2018	J	`jnl`	Composite Optimization by Nonconvex Majorization-Minimization. SIAM J. Imaging Sci. Jonas Geiping, Michael Möller
2017	—	`conf`	Multiframe Motion Coupling for Video Super Resolution. EMMCVPR Jonas Geiping, Hendrik Dirks, Daniel Cremers, Michael Möller
2016	J	`jnl`	Multiframe Motion Coupling via Infimal Convolution Regularization for Video Super Resolution. CoRR Hendrik Dirks, Jonas Geiping, Daniel Cremers, Michael Möller