| A watermark for large language models J Kirchenbauer, J Geiping, Y Wen, J Katz, I Miers, T Goldstein International Conference on Machine Learning (ICML) 2023, 2023 | 312 | 2023 |
| Hard prompts made easy: Gradient-based discrete optimization for prompt tuning and discovery Y Wen, N Jain, J Kirchenbauer, M Goldblum, J Geiping, T Goldstein Conference on Neural Information Processing Systems (NeurIPS) 2023, 2023 | 97 | 2023 |
| Baseline defenses for adversarial attacks against aligned language models N Jain, A Schwarzschild, Y Wen, G Somepalli, J Kirchenbauer, P Chiang, ... arXiv preprint arXiv:2309.00614, 2023 | 95* | 2023 |
| On the Reliability of Watermarks for Large Language Models J Kirchenbauer, J Geiping, Y Wen, M Shu, K Saifullah, K Kong, ... International Conference on Learning Representations (ICLR) 2024, 2024 | 64* | 2024 |
| Fishing for User Data in Large-Batch Federated Learning via Gradient Magnification Y Wen, J Geiping, L Fowl, M Goldblum, T Goldstein International Conference on Machine Learning (ICML) 2022, 2022 | 59 | 2022 |
| Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust Y Wen, J Kirchenbauer, J Geiping, T Goldstein Conference on Neural Information Processing Systems (NeurIPS) 2023, 2023 | 37* | 2023 |
| Decepticons: Corrupted transformers breach privacy in federated learning for language models L Fowl, J Geiping, S Reich, Y Wen, W Czaja, M Goldblum, T Goldstein International Conference on Learning Representations (ICLR) 2023, 2022 | 32 | 2022 |
| NEFTune: Noisy Embeddings Improve Instruction Finetuning N Jain, P Chiang, Y Wen, J Kirchenbauer, HM Chu, G Somepalli, ... International Conference on Learning Representations (ICLR) 2024, 2024 | 22* | 2024 |
| Canary in a Coalmine: Better Membership Inference with Ensembled Adversarial Queries Y Wen, A Bansal, H Kazemi, E Borgnia, M Goldblum, J Geiping, ... International Conference on Learning Representations (ICLR) 2023, 2022 | 15 | 2022 |
| Bring your own data! self-supervised evaluation for large language models N Jain, K Saifullah, Y Wen, J Kirchenbauer, M Shu, A Saha, M Goldblum, ... arXiv preprint arXiv:2306.13651, 2023 | 13 | 2023 |
| Thinking Two Moves Ahead: Anticipating Other Users Improves Backdoor Attacks in Federated Learning Y Wen, J Geiping, L Fowl, H Souri, R Chellappa, M Goldblum, T Goldstein AdvML Frontiers Workshop, ICML 2022, 2022 | 10 | 2022 |
| Coercing LLMs to do and reveal (almost) anything J Geiping, A Stein, M Shu, K Saifullah, Y Wen, T Goldstein arXiv preprint arXiv:2402.14020, 2024 | 2 | 2024 |
| Benchmarking the Robustness of Image Watermarks B An, M Ding, T Rabbani, A Agrawal, Y Xu, C Deng, S Zhu, A Mohamed, ... arXiv preprint arXiv:2401.08573, 2024 | 1 | 2024 |
| Detecting, Explaining, and Mitigating Memorization in Diffusion Models Y Wen, Y Liu, C Chen, L Lyu International Conference on Learning Representations (ICLR) 2024, 2024 | 1 | 2024 |
| Seeing in Words: Learning to Classify through Language Bottlenecks K Saifullah, Y Wen, J Geiping, M Goldblum, T Goldstein Tiny Paper at ICLR 2023, 2023 | 1 | 2023 |
| Learning to Discover Curbside Parking Spaces from Vehicle Trajectories Y Wen, J Huang, C Zhu, M Fan, Y Li 2019 IEEE International Conference on Big Data (Big Data), 1537-1546, 2019 | 1 | 2019 |
| Privacy Backdoors: Enhancing Membership Inference through Poisoning Pre-trained Models Y Wen, L Marchyok, S Hong, J Geiping, T Goldstein, N Carlini arXiv preprint arXiv:2404.01231, 2024 | | 2024 |
| Styx: Adaptive Poisoning Attacks against Byzantine-Robust Defenses in Federated Learning Y Wen, J Geiping, M Goldblum, T Goldstein ICASSP 2023-2023 IEEE International Conference on Acoustics, Speech and …, 2023 | | 2023 |
Jonas GeipingResearch Group Leader ELLIS Institute & MPI-IS TübingenVerified email at tuebingen.mpg.de
