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John Kirchenbauer
John Kirchenbauer
Geverifieerd e-mailadres voor umd.edu
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A watermark for large language models
J Kirchenbauer, J Geiping, Y Wen, J Katz, I Miers, T Goldstein
arXiv preprint arXiv:2301.10226, 2023
2352023
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
Advances in Neural Information Processing Systems 36, 2024
762024
Kezhi Kong, Kasun Fernando, Aniruddha Saha, Micah Goldblum, and Tom Goldstein. On the reliability of watermarks for large language models
J Kirchenbauer, J Geiping, Y Wen, M Shu, K Saifullah
arXiv preprint arXiv:2306.04634, 2023
362023
Tree-Ring Watermarks: Fingerprints for Diffusion Images that are Invisible and Robust
Y Wen, J Kirchenbauer, J Geiping, T Goldstein
arXiv preprint arXiv:2305.20030, 2023
212023
On the Reliability of Watermarks for Large Language Models
J Kirchenbauer, J Geiping, Y Wen, M Shu, K Saifullah, K Kong, ...
arXiv preprint arXiv:2306.04634, 2023
162023
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
122023
A closer look at distribution shifts and out-of-distribution generalization on graphs
M Ding, K Kong, J Chen, J Kirchenbauer, M Goldblum, D Wipf, F Huang, ...
122021
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
102023
GOAT: A Global Transformer on Large-scale Graphs
K Kong, J Chen, J Kirchenbauer, R Ni, CB Bruss, T Goldstein
82023
Neftune: Noisy embeddings improve instruction finetuning
N Jain, P Chiang, Y Wen, J Kirchenbauer, HM Chu, G Somepalli, ...
arXiv preprint arXiv:2310.05914, 2023
62023
A watermark for large language models. ArXiv
J Kirchenbauer, J Geiping, Y Wen, J Katz, I Miers, T Goldstein
arXiv preprint arXiv:2301.10226, 2023
52023
Avi Schwarzschild, Aniruddha Saha, Micah Goldblum, Jonas Geiping, and Tom Goldstein. 2023. NEFTune: Noisy embeddings improve instruction finetuning
N Jain, P yeh Chiang, Y Wen, J Kirchenbauer, HM Chu, G Somepalli, ...
arXiv preprint arXiv:2310.05914, 0
5
Tree-Rings Watermarks: Invisible Fingerprints for Diffusion Images
Y Wen, J Kirchenbauer, J Geiping, T Goldstein
Advances in Neural Information Processing Systems 36, 2024
32024
Knowing When You Don't Know: Quantifying and Reasoning about Uncertainty in Machine Learning Models
E Heim, J Kirchenbauer, J Helland, J Oaks, A Singh, Z Lipton
12022
What is Your Metric Telling You? Evaluating Classifier Calibration under Context-Specific Definitions of Reliability
J Kirchenbauer, J Oaks, E Heim
12022
17084
J Kirchenbauer, J Geiping, Y Wen, J Katz, I Miers, T Goldstein
Proceedings of the 40th International Conference on Machine Learning, 17061 …, 2023
2023
How to Do a Vocab Swap? A Study of Embedding Replacement for Pre-trained Transformers
N Jain, J Kirchenbauer, J Geiping, T Goldstein
2022
In Search of Out-of-Distribution Generalization on Graphs
M Ding, K Kong, J Chen, J Kirchenbauer, M Goldblum, D Wipf, F Huang, ...
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Artikelen 1–18