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Yuxin Wen
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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
3302023
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
107*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
1072023
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
69*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
632022
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
412023
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
332022
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
23*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
172022
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
152023
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
102022
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
42024
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
32024
Detecting, Explaining, and Mitigating Memorization in Diffusion Models
Y Wen, Y Liu, C Chen, L Lyu
International Conference on Learning Representations (ICLR) 2024, 2024
22024
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
12023
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
12019
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
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