Mariya Toneva
Title
Cited by
Cited by
Year
The physical presence of a robot tutor increases cognitive learning gains
D Leyzberg, S Spaulding, M Toneva, B Scassellati
Proceedings of the annual meeting of the cognitive science society 34 (34), 2012
2532012
An Empirical Study of Example Forgetting during Deep Neural Network Learning
M Toneva, A Sordoni, R Tachet des Combes, A Trischler, Y Bengio, ...
International Conference on Learning Representations, 2019
1032019
Robot gaze does not reflexively cue human attention
H Admoni, C Bank, J Tan, M Toneva, B Scassellati
Proceedings of the Annual Meeting of the Cognitive Science Society 33 (33), 2011
672011
Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain)
M Toneva, L Wehbe
Neural Information Processing Systems 33 (33), 2019
552019
Inducing brain-relevant bias in natural language processing models
D Schwartz, M Toneva, L Wehbe
Neural Information Processing Systems 33 (33), 2019
272019
Applying artificial vision models to human scene understanding
EM Aminoff, M Toneva, A Shrivastava, X Chen, I Misra, A Gupta, MJ Tarr
Frontiers in computational neuroscience 9, 8, 2015
82015
An exploration of social grouping in robots: Effects of behavioral mimicry, appearance, and eye gaze
A Nawroj, M Toneva, H Admoni, B Scassellati
Proceedings of the Annual Meeting of the Cognitive Science Society 36 (36), 2014
62014
Proceedings of the 33rd annual conference of the cognitive science society
H Admoni, C Bank, J Tan, M Toneva, B Scassellati
52011
Combining computational controls with natural text reveals new aspects of meaning composition
M Toneva, TM Mitchell, L Wehbe
bioRxiv, 2020
32020
Modeling Task Effects on Meaning Representation in the Brain via Zero-Shot MEG Prediction
M Toneva, O Stretcu, B Poczos, L Wehbe, TM Mitchell
Neural Information Processing Systems 34 (34), 2020
12020
A roadmap to reverse engineering real-world generalization by combining naturalistic paradigms, deep sampling, and predictive computational models
P Herholz, E Fortier, M Toneva, N Farrugia, L Wehbe, V Borghesani
arXiv preprint arXiv:2108.10231, 2021
2021
Does injecting linguistic structure into language models lead to better alignment with brain recordings?
M Abdou, AV González, M Toneva, D Hershcovich, A Søgaard
arXiv preprint arXiv:2101.12608, 2021
2021
The meaning that emerges from combining words is robustly localizable in space but not in time
M Toneva, TM Mitchell, L Wehbe
bioRxiv, 2020
2020
Word Length Processing via Region-to-Region Connectivity
M Toneva
2018
Scene-Space Encoding within the Functional Scene-Selective Network
E Aminoff, M Toneva, A Gupta, M Tarr
Journal of Vision 15 (12), 507-507, 2015
2015
Towards a model for mid-level feature representation of scenes
M Toneva, E Aminoff, A Gupta, M Tarr
Journal of Vision 14 (10), 363-363, 2014
2014
Single-trial MEG data can be denoised through cross-subject predictive modeling
S Ravishankar, M Toneva, L Wehbe
Frontiers in Computational Neuroscience, 82, 0
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Articles 1–17