Tom Goldstein

ORCID

Publication Activity (10 Years)

Years Active: 2004-2024
Publications (10 Years): 320

Top Venues

Publications

Bang An, Mucong Ding, Tahseen Rabbani, Aakriti Agrawal, Yuancheng Xu, Chenghao Deng, Sicheng Zhu, Abdirisak Mohamed, Yuxin Wen, Tom Goldstein, Furong Huang
Benchmarking the Robustness of Image Watermarks. CoRR (2024)
Lichang Chen, Chen Zhu, Davit Soselia, Jiuhai Chen, Tianyi Zhou, Tom Goldstein, Heng Huang, Mohammad Shoeybi, Bryan Catanzaro
ODIN: Disentangled Reward Mitigates Hacking in RLHF. CoRR (2024)
Yuancheng Xu, Jiarui Yao, Manli Shu, Yanchao Sun, Zichu Wu, Ning Yu, Tom Goldstein, Furong Huang
Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language Models. CoRR (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, Vasu Singla, Micah Goldblum, Jonas Geiping, Tom Goldstein
Diffusion Art or Digital Forgery? Investigating Data Replication in Diffusion Models. CVPR (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)
Yuancheng Xu, Yanchao Sun, Micah Goldblum, Tom Goldstein, Furong Huang
Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness. CoRR (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)
Roman Levin, Valeriia Cherepanova, Avi Schwarzschild, Arpit Bansal, C. Bayan Bruss, Tom Goldstein, Andrew Gordon Wilson, Micah Goldblum
Transfer Learning with Deep Tabular Models. ICLR (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)
Micah Goldblum, Hossein Souri, Renkun Ni, Manli Shu, Viraj Prabhu, Gowthami Somepalli, Prithvijit Chattopadhyay, Mark Ibrahim, Adrien Bardes, Judy Hoffman, Rama Chellappa, Andrew Gordon Wilson, Tom Goldstein
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks. CoRR (2023)
Kezhi Kong, Jiuhai Chen, John Kirchenbauer, Renkun Ni, C. Bayan Bruss, Tom Goldstein
GOAT: A Global Transformer on Large-scale Graphs. ICML (2023)
Yuxin Wen, John Kirchenbauer, Jonas Geiping, Tom Goldstein
Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust. CoRR (2023)
Alex Stein, Avi Schwarzschild, Michael J. Curry, Tom Goldstein, John P. Dickerson
Neural Auctions Compromise Bidder Information. 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)
Ping-yeh Chiang, Yipin Zhou, Omid Poursaeed, Satya Narayan Shukla, Ashish Shah, Tom Goldstein, Ser-Nam Lim
Universal Pyramid Adversarial Training for Improved ViT Performance. CoRR (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)
Yuancheng Xu, Yanchao Sun, Micah Goldblum, Tom Goldstein, Furong Huang
Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness. ICLR (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)
Micah Goldblum, Anima Anandkumar, Richard G. Baraniuk, Tom Goldstein, Kyunghyun Cho, Zachary C. Lipton, Melanie Mitchell, Preetum Nakkiran, Max Welling, Andrew Gordon Wilson
Perspectives on the State and Future of Deep Learning - 2023. 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)
Lichang Chen, Jiuhai Chen, Tom Goldstein, Heng Huang, Tianyi Zhou
InstructZero: Efficient Instruction Optimization for Black-Box Large Language Models. CoRR (2023)
Aounon Kumar, Alexander Levine, Tom Goldstein, Soheil Feizi
Provable Robustness against Wasserstein Distribution Shifts via Input Randomization. ICLR (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)
Valeriia Cherepanova, Steven Reich, Samuel Dooley, Hossein Souri, John P. Dickerson, Micah Goldblum, Tom Goldstein
A Deep Dive into Dataset Imbalance and Bias in Face Identification. AIES (2023)
Pedro Sandoval Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein
What Can We Learn from Unlearnable Datasets? NeurIPS (2023)
Micah Goldblum, Hossein Souri, Renkun Ni, Manli Shu, Viraj Prabhu, Gowthami Somepalli, Prithvijit Chattopadhyay, Mark Ibrahim, Adrien Bardes, Judy Hoffman, Rama Chellappa, Andrew Gordon Wilson, Tom Goldstein
Battle of the Backbones: A Large-Scale Comparison of Pretrained Models across Computer Vision Tasks. NeurIPS (2023)
Zhipeng Wei, Jingjing Chen, Micah Goldblum, Zuxuan Wu, Tom Goldstein, Yu-Gang Jiang, Larry S. Davis
Towards Transferable Adversarial Attacks on Image and Video Transformers. IEEE Trans. Image Process. 32 (2023)
Vasu Singla, Pedro Sandoval Segura, Micah Goldblum, Jonas Geiping, Tom Goldstein
A Simple and Efficient Baseline for Data Attribution on Images. CoRR (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)
Shishira R. Maiya, Max Ehrlich, Vatsal Agarwal, Ser-Nam Lim, Tom Goldstein, Abhinav Shrivastava
Unifying the Harmonic Analysis of Adversarial Attacks and Robustness. BMVC (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)
Micah Goldblum, Dimitris Tsipras, Chulin Xie, Xinyun Chen, Avi Schwarzschild, Dawn Song, Aleksander Madry, Bo Li, Tom Goldstein
Dataset Security for Machine Learning: Data Poisoning, Backdoor Attacks, and Defenses. IEEE Trans. Pattern Anal. Mach. Intell. 45 (2) (2023)
Zhipeng Wei, Jingjing Chen, Micah Goldblum, Zuxuan Wu, Tom Goldstein, Yu-Gang Jiang
Towards Transferable Adversarial Attacks on Vision Transformers. AAAI (2022)
Jonas Geiping, Micah Goldblum, Phillip Pope, Michael Moeller, Tom Goldstein
Stochastic Training is Not Necessary for Generalization. ICLR (2022)
Harrison Foley, Liam Fowl, Tom Goldstein, Gavin Taylor
Execute Order 66: Targeted Data Poisoning for Reinforcement Learning. CoRR (2022)
Samuel Dooley, George Z. Wei, Tom Goldstein, John P. Dickerson
Are Commercial Face Detection Models as Biased as Academic Models? CoRR (2022)
Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein
Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. CVPR (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)
Roman Levin, Manli Shu, Eitan Borgnia, Furong Huang, Micah Goldblum, Tom Goldstein
Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability. NeurIPS (2022)
Arpit Bansal, Ping-yeh Chiang, Michael J. Curry, Rajiv Jain, Curtis Wigington, Varun Manjunatha, John P. Dickerson, Tom Goldstein
Certified Neural Network Watermarks with Randomized Smoothing. CoRR (2022)
Amin Ghiasi, Hamid Kazemi, Steven Reich, Chen Zhu, Micah Goldblum, Tom Goldstein
Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations. CoRR (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)
Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Soji Adeshina, Yangkun Wang, Tom Goldstein, David Wipf
Does your graph need a confidence boost? Convergent boosted smoothing on graphs with tabular node features. 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)
Arpit Bansal, Avi Schwarzschild, Eitan Borgnia, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein
End-to-end Algorithm Synthesis with Recurrent Networks: Extrapolation without Overthinking. NeurIPS (2022)
Amin Ghiasi, Hamid Kazemi, Eitan Borgnia, Steven Reich, Manli Shu, Micah Goldblum, Andrew Gordon Wilson, Tom Goldstein
What do Vision Transformers Learn? A Visual Exploration. 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)
Manli Shu, Weili Nie, De-An Huang, Zhiding Yu, Tom Goldstein, Anima Anandkumar, Chaowei Xiao
Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models. CoRR (2022)
Hossein Souri, Liam Fowl, Rama Chellappa, Micah Goldblum, Tom Goldstein
Sleeper Agent: Scalable Hidden Trigger Backdoors for Neural Networks Trained from Scratch. NeurIPS (2022)
Pedro Sandoval Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein, David Jacobs
Autoregressive Perturbations for Data Poisoning. NeurIPS (2022)
Renkun Ni, Manli Shu, Hossein Souri, Micah Goldblum, Tom Goldstein
The Close Relationship Between Contrastive Learning and Meta-Learning. ICLR (2022)
Arpit Bansal, Ping-Yeh Chiang, Michael J. Curry, Rajiv Jain, Curtis Wigington, Varun Manjunatha, John P. Dickerson, Tom Goldstein
Certified Neural Network Watermarks with Randomized Smoothing. ICML (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)
Jiuhai Chen, Jonas Mueller, Vassilis N. Ioannidis, Tom Goldstein, David Wipf
A Robust Stacking Framework for Training Deep Graph Models with Multifaceted Node Features. 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)
Kezhi Kong, Guohao Li, Mucong Ding, Zuxuan Wu, Chen Zhu, Bernard Ghanem, Gavin Taylor, Tom Goldstein
Robust Optimization as Data Augmentation for Large-scale Graphs. CVPR (2022)
Roman Levin, Valeriia Cherepanova, Avi Schwarzschild, Arpit Bansal, C. Bayan Bruss, Tom Goldstein, Andrew Gordon Wilson, Micah Goldblum
Transfer Learning with Deep Tabular Models. CoRR (2022)
Chen Zhu, Zheng Xu, Mingqing Chen, Jakub Konecný, Andrew Hard, Tom Goldstein
Diurnal or Nocturnal? Federated Learning of Multi-branch Networks from Periodically Shifting Distributions. ICLR (2022)
Michael J. Curry, Uro Lyi, Tom Goldstein, John P. Dickerson
Learning Revenue-Maximizing Auctions With Differentiable Matching. AISTATS (2022)
Haochuan Song, Tom Goldstein, Xiaohu You, Chuan Zhang, Olav Tirkkonen, Christoph Studer
Joint Channel Estimation and Data Detection in Cell-Free Massive MU-MIMO Systems. IEEE Trans. Wirel. Commun. 21 (6) (2022)
Gowthami Somepalli, Liam Fowl, Arpit Bansal, Ping-Yeh Chiang, Yehuda Dar, Richard G. Baraniuk, Micah Goldblum, Tom Goldstein
Can Neural Nets Learn the Same Model Twice? Investigating Reproducibility and Double Descent from the Decision Boundary Perspective. CoRR (2022)
Pedro Sandoval Segura, Vasu Singla, Jonas Geiping, Micah Goldblum, Tom Goldstein, David W. Jacobs
Autoregressive Perturbations for Data Poisoning. CoRR (2022)
Avi Schwarzschild, Arjun Gupta, Amin Ghiasi, Micah Goldblum, Tom Goldstein
The Uncanny Similarity of Recurrence and Depth. ICLR (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)
Aounon Kumar, Alexander Levine, Tom Goldstein, Soheil Feizi
Certifying Model Accuracy under Distribution Shifts. 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)
Manli Shu, Weili Nie, De-An Huang, Zhiding Yu, Tom Goldstein, Anima Anandkumar, Chaowei Xiao
Test-Time Prompt Tuning for Zero-Shot Generalization in Vision-Language Models. NeurIPS (2022)
Amin Ghiasi, Hamid Kazemi, Steven Reich, Chen Zhu, Micah Goldblum, Tom Goldstein
Plug-In Inversion: Model-Agnostic Inversion for Vision with Data Augmentations. ICML (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)
Samuel Dooley, George Z. Wei, Tom Goldstein, John Dickerson
Robustness Disparities in Face Detection. NeurIPS (2022)
Samuel Dooley, George Z. Wei, Tom Goldstein, John P. Dickerson
Robustness Disparities in Face Detection. CoRR (2022)
Arpit Bansal, Avi Schwarzschild, Eitan Borgnia, Zeyad Emam, Furong Huang, Micah Goldblum, Tom Goldstein
End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking. CoRR (2022)
Valeriia Cherepanova, Steven Reich, Samuel Dooley, Hossein Souri, Micah Goldblum, Tom Goldstein
A Deep Dive into Dataset Imbalance and Bias in Face Identification. CoRR (2022)
Avi Schwarzschild, Eitan Borgnia, Arjun Gupta, Furong Huang, Uzi Vishkin, Micah Goldblum, Tom Goldstein
Can You Learn an Algorithm? Generalizing from Easy to Hard Problems with Recurrent Networks. NeurIPS (2021)

Tom Goldstein.css-eqlu8i{font-size:small;padding-left:4px;}

Publication Activity (10 Years)

Top Topics

Top Venues

Tom Goldstein