| Cold diffusion: Inverting arbitrary image transforms without noise A Bansal, E Borgnia, HM Chu, J Li, H Kazemi, F Huang, M Goldblum, ... Advances in Neural Information Processing Systems 36, 2024 | 186 | 2024 |
| What do vision transformers learn? A visual exploration H Kazemi, A Ghiasi, E Borgnia, S Reich, M Shu, M Goldblum, AG Wilson, ... | 53* | |
| Canary in a coalmine: Better membership inference with ensembled adversarial queries Y Wen, A Bansal, H Kazemi, E Borgnia, M Goldblum, J Geiping, ... arXiv preprint arXiv:2210.10750, 2022 | 22 | 2022 |
| Plug-in inversion: Model-agnostic inversion for vision with data augmentations A Ghiasi, H Kazemi, S Reich, C Zhu, M Goldblum, T Goldstein | 10 | 2022 |
| Spotting llms with binoculars: Zero-shot detection of machine-generated text A Hans, A Schwarzschild, V Cherepanova, H Kazemi, A Saha, ... arXiv preprint arXiv:2401.12070, 2024 | 5 | 2024 |
| Feature Sonification: An investigation on the features learned for Automatic Speech Recognition 2021 A Ghiasi, H Kazemi, R Huang, E Liu, M Goldblum, T Goldstein https://sonification.cs.umd.edu/, 0 | 2 | |
| What do we learn from inverting CLIP models? H Kazemi, A Chegini, J Geiping, S Feizi, T Goldstein arXiv preprint arXiv:2403.02580, 2024 | 1 | 2024 |
| Be like a Goldfish, Don't Memorize! Mitigating Memorization in Generative LLMs A Hans, Y Wen, N Jain, J Kirchenbauer, H Kazemi, P Singhania, S Singh, ... arXiv preprint arXiv:2406.10209, 2024 | | 2024 |
| Generating Potent Poisons and Backdoors from Scratch with Guided Diffusion H Souri, A Bansal, H Kazemi, L Fowl, A Saha, J Geiping, AG Wilson, ... arXiv preprint arXiv:2403.16365, 2024 | | 2024 |
Tom GoldsteinVolpi-Cupal Professor of Computer Science, University of MarylandVerified email at cs.umd.edu
