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Ilia Sucholutsky
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Year
Soft-Label Dataset Distillation and Text Dataset Distillation
I Sucholutsky, M Schonlau
2021 International Joint Conference on Neural Networks, 2019
982019
Text mining with n-gram variables
M Schonlau, N Guenther, I Sucholutsky
The Stata Journal 17 (4), 866-881, 2017
77*2017
GPT is an effective tool for multilingual psychological text analysis
S Rathje, DM Mirea, I Sucholutsky, R Marjieh, C Robertson, JJ Van Bavel
PsyArXiv, 2023
582023
'Less Than One'-Shot Learning: Learning N Classes From M< N Samples
I Sucholutsky, M Schonlau
Proceedings of the AAAI Conference on Artificial Intelligence 35 (11), 9739-9746, 2021
542021
Words are all you need? Language as an approximation for human similarity judgments
R Marjieh, P Van Rijn, I Sucholutsky, TR Sumers, H Lee, TL Griffiths, ...
arXiv preprint arXiv:2206.04105, 2022
21*2022
Human uncertainty in concept-based ai systems
KM Collins, M Barker, M Espinosa Zarlenga, N Raman, U Bhatt, M Jamnik, ...
Proceedings of the 2023 AAAI/ACM Conference on AI, Ethics, and Society, 869-889, 2023
172023
What language reveals about perception: Distilling psychophysical knowledge from large language models
R Marjieh, I Sucholutsky, P van Rijn, N Jacoby, T Griffiths
Proceedings of the Annual Meeting of the Cognitive Science Society 45 (45), 2023
172023
Alignment with human representations supports robust few-shot learning
I Sucholutsky, T Griffiths
Advances in Neural Information Processing Systems 36, 2024
162024
Getting aligned on representational alignment
I Sucholutsky, L Muttenthaler, A Weller, A Peng, A Bobu, B Kim, BC Love, ...
arXiv preprint arXiv:2310.13018, 2023
162023
Secdd: Efficient and secure method for remotely training neural networks (student abstract)
I Sucholutsky, M Schonlau
Proceedings of the AAAI Conference on Artificial Intelligence 35 (18), 15897 …, 2021
142021
Predicting human similarity judgments using large language models
R Marjieh, I Sucholutsky, TR Sumers, N Jacoby, TL Griffiths
arXiv preprint arXiv:2202.04728, 2022
132022
Large language models meet cognitive science: Llms as tools, models, and participants
M Hardy, I Sucholutsky, B Thompson, T Griffiths
Proceedings of the annual meeting of the cognitive science society 45 (45), 2023
102023
Deep Learning for System Trace Restoration
I Sucholutsky, A Narayan, M Schonlau, S Fischmeister
2019 International Joint Conference on Neural Networks (IJCNN), 2019
92019
On the informativeness of supervision signals
I Sucholutsky, RM Battleday, KM Collins, R Marjieh, J Peterson, P Singh, ...
Uncertainty in Artificial Intelligence, 2036-2046, 2023
82023
Human-in-the-Loop Mixup
KM Collins, U Bhatt, W Liu, V Piratla, I Sucholutsky, B Love, A Weller
Uncertainty in Artificial Intelligence, 2023, 2022
8*2022
Large language models predict human sensory judgments across six modalities
R Marjieh, I Sucholutsky, P van Rijn, N Jacoby, TL Griffiths
arXiv preprint arXiv:2302.01308, 2023
52023
Can Humans Do Less-Than-One-Shot Learning?
M Malaviya, I Sucholutsky, K Oktar, TL Griffiths
arXiv preprint arXiv:2202.04670, 2022
52022
One Line To Rule Them All: Generating LO-Shot Soft-Label Prototypes
I Sucholutsky, NH Kim, RP Browne, M Schonlau
2021 International Joint Conference on Neural Networks (IJCNN), 1-8, 2021
52021
Concept alignment as a prerequisite for value alignment
S Rane, M Ho, I Sucholutsky, TL Griffiths
arXiv preprint arXiv:2310.20059, 2023
42023
Pay attention and you won’t lose it: a deep learning approach to sequence imputation
I Sucholutsky, A Narayan, M Schonlau, S Fischmeister
PeerJ Computer Science 5 (e210), 2019
42019
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Articles 1–20