Leila Wehbe
Leila Wehbe
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Cited by
Cited by
Simultaneously uncovering the patterns of brain regions involved in different story reading subprocesses
L Wehbe, B Murphy, P Talukdar, A Fyshe, A Ramdas, T Mitchell
PloS one 9 (11), e112575, 2014
Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain)
M Toneva, L Wehbe
Advances in neural information processing systems 32, 2019
Tracking neural coding of perceptual and semantic features of concrete nouns
G Sudre, D Pomerleau, M Palatucci, L Wehbe, A Fyshe, R Salmelin, ...
NeuroImage 62 (1), 451-463, 2012
Aligning context-based statistical models of language with brain activity during reading
L Wehbe, A Vaswani, K Knight, T Mitchell
Proceedings of the 2014 conference on empirical methods in natural language …, 2014
Inducing brain-relevant bias in natural language processing models
D Schwartz, M Toneva, L Wehbe
Advances in neural information processing systems 32, 2019
A compositional and interpretable semantic space
A Fyshe, L Wehbe, P Talukdar, B Murphy, T Mitchell
Proceedings of the 2015 conference of the north american chapter of the …, 2015
Incremental language comprehension difficulty predicts activity in the language network but not the multiple demand network
L Wehbe, IA Blank, C Shain, R Futrell, R Levy, T von der Malsburg, ...
Cerebral Cortex 31 (9), 4006-4023, 2021
Combining computational controls with natural text reveals aspects of meaning composition
M Toneva, TM Mitchell, L Wehbe
Nature computational science 2 (11), 745-757, 2022
The lexical semantics of adjective–noun phrases in the human brain
A Fyshe, G Sudre, L Wehbe, N Rafidi, TM Mitchell
Human brain mapping 40 (15), 4457-4469, 2019
Can fMRI reveal the representation of syntactic structure in the brain?
AJ Reddy, L Wehbe
Advances in neural information processing systems 34, 9843-9856, 2021
Neural taskonomy: Inferring the similarity of task-derived representations from brain activity
A Wang, M Tarr, L Wehbe
Advances in neural information processing systems 32, 2019
Better models of human high-level visual cortex emerge from natural language supervision with a large and diverse dataset
AY Wang, K Kay, T Naselaris, MJ Tarr, L Wehbe
Nature Machine Intelligence 5 (12), 1415-1426, 2023
Selectivity for food in human ventral visual cortex
N Jain, A Wang, MM Henderson, R Lin, JS Prince, MJ Tarr, L Wehbe
Communications Biology 6 (1), 175, 2023
Computational language modeling and the promise of in silico experimentation
S Jain, VA Vo, L Wehbe, AG Huth
Neurobiology of Language 5 (1), 80-106, 2024
Modeling task effects on meaning representation in the brain via zero-shot meg prediction
M Toneva, O Stretcu, B Póczos, L Wehbe, TM Mitchell
Advances in Neural Information Processing Systems 33, 5284-5295, 2020
A deep learning model for automated classification of intraoperative continuous emg
X Zha, L Wehbe, RJ Sclabassi, Z Mace, YV Liang, A Yu, J Leonardo, ...
IEEE transactions on medical robotics and bionics 3 (1), 44-52, 2020
Semantic representations during language comprehension are affected by context
F Deniz, C Tseng, L Wehbe, TD la Tour, JL Gallant
Journal of Neuroscience 43 (17), 3144-3158, 2023
Decoding language from the brain
B Murphy, L Wehbe, A Fyshe
Language, cognition, and computational models, 53-80, 2018
Regularized brain reading with shrinkage and smoothing
L Wehbe, A Ramdas, RC Steorts, CR Shalizi
The annals of applied statistics 9 (4), 1997, 2015
Nonparametric independence testing for small sample sizes
A Ramdas, L Wehbe
24th International Conference on Artificial Intelligence, 3777-3783, 2015
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