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Yannic Kilcher
Yannic Kilcher
PhD Student, ETH Zurich
Verified email at inf.ethz.ch
Title
Cited by
Cited by
Year
Openassistant conversations-democratizing large language model alignment
A Köpf, Y Kilcher, D von Rütte, S Anagnostidis, ZR Tam, K Stevens, ...
Advances in Neural Information Processing Systems 36, 2024
1842024
The odds are odd: A statistical test for detecting adversarial examples
K Roth, Y Kilcher, T Hofmann
International Conference on Machine Learning, 5498-5507, 2019
1822019
Audio based bird species identification using deep learning techniques
E Sprengel, M Jaggi, Y Kilcher, T Hofmann
LifeCLEF 2016, 547-559, 2016
1542016
How does BERT capture semantics? A closer look at polysemous words
D Yenicelik, F Schmidt, Y Kilcher
Proceedings of the Third BlackboxNLP Workshop on Analyzing and Interpreting …, 2020
562020
Adversarial training is a form of data-dependent operator norm regularization
K Roth, Y Kilcher, T Hofmann
Advances in Neural Information Processing Systems 33, 14973-14985, 2020
462020
Semantic interpolation in implicit models
Y Kilcher, A Lucchi, T Hofmann
arXiv preprint arXiv:1710.11381, 2017
262017
FIGARO: Generating symbolic music with fine-grained artistic control
D von Rütte, L Biggio, Y Kilcher, T Hofmann
arXiv preprint arXiv:2201.10936, 2022
252022
Boosting search engines with interactive agents
L Adolphs, B Boerschinger, C Buck, MC Huebscher, M Ciaramita, ...
arXiv preprint arXiv:2109.00527, 2021
242021
Scalable adaptive stochastic optimization using random projections
G Krummenacher, B McWilliams, Y Kilcher, JM Buhmann, N Meinshausen
Advances in Neural Information Processing Systems 29, 2016
182016
Openassistant conversations-democratizing large language model alignment. CoRR, abs/2304.07327, 2023. doi: 10.48550
A Köpf, Y Kilcher, D von Rütte, S Anagnostidis, ZR Tam, K Stevens, ...
arXiv preprint arXiv.2304.07327, 0
11
Adversarial training generalizes data-dependent spectral norm regularization
K Roth, Y Kilcher, T Hofmann
102019
FIGARO: Controllable Music Generation using Learned and Expert Features
D von Rütte, L Biggio, Y Kilcher, T Hofmann
The Eleventh International Conference on Learning Representations, 2022
92022
Generative minimization networks: Training GANs without competition
P Grnarova, Y Kilcher, KY Levy, A Lucchi, T Hofmann
arXiv preprint arXiv:2103.12685, 2021
62021
The best defense is a good offense: Countering black box attacks by predicting slightly wrong labels
Y Kilcher, T Hofmann
arXiv preprint arXiv:1711.05475, 2017
32017
Rethinking Neural Networks With Benford's Law
SK Sahu, A Java, A Shaikh, Y Kilcher
arXiv preprint arXiv:2102.03313, 2021
22021
Generator reversal
Y Kilcher, A Lucchi, T Hofmann
arXiv preprint arXiv:1707.09241, 2017
22017
Boosting search engines with interactive agents
B Boerschinger, CCF Buck, LJG Espeholt, L Adolphs, LS Saralegui, ...
12022
Meta answering for machine reading
B Borschinger, J Boyd-Graber, C Buck, J Bulian, M Ciaramita, ...
arXiv preprint arXiv:1911.04156, 2019
12019
Flexible Prior Distributions for Deep Generative Models
Y Kilcher, A Lucchi, T Hofmann
arXiv preprint arXiv:1710.11383, 2017
12017
Parametrizing filters of a CNN with a GAN
Y Kilcher, G Becigneul, T Hofmann
arXiv preprint arXiv:1710.11386, 2017
12017
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