| 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 | 507 | 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 | 194* | 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 | 164 | 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 | 124* | 2024 |
| 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 | 86* | 2023 |
| 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 | 81 | 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 | 56* | 2024 |
| 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 | 48 | 2022 |
| 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 | 26 | 2022 |
| Detecting, Explaining, and Mitigating Memorization in Diffusion Models Y Wen, Y Liu, C Chen, L Lyu International Conference on Learning Representations (ICLR) 2024, 2024 | 21 | 2024 |
| 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, ... Conference on Language Modeling (COLM) 2024, 2023 | 20 | 2023 |
| 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 | 19 | 2024 |
| Benchmarking the Robustness of Image Watermarks B An, M Ding, T Rabbani, A Agrawal, Y Xu, C Deng, S Zhu, A Mohamed, ... International Conference on Machine Learning (ICML) 2024, 2024 | 13 | 2024 |
| 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 |
| Privacy backdoors: Enhancing membership inference through poisoning pre-trained models Y Wen, L Marchyok, S Hong, J Geiping, T Goldstein, N Carlini Conference on Neural Information Processing Systems (NeurIPS) 2024, 2024 | 6 | 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, ... Conference on Neural Information Processing Systems (NeurIPS) 2024, 2024 | 3* | 2024 |
| Is Synthetic Image Useful for Transfer Learning? An Investigation into Data Generation, Volume, and Utilization Y Li, X Dong, C Chen, J Li, Y Wen, M Spranger, L Lyu arXiv preprint arXiv:2403.19866, 2024 | 3 | 2024 |
| GenQA: Generating Millions of Instructions from a Handful of Prompts J Chen, R Qadri, Y Wen, N Jain, J Kirchenbauer, T Zhou, T Goldstein arXiv preprint arXiv:2406.10323, 2024 | 2 | 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 | 2 | 2023 |
| 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 |
Jonas GeipingELLIS Institute Tübingen & Max Planck Institute for Intelligent SystemsGeverifieerd e-mailadres voor tuebingen.mpg.de
