22 citations · 46 across the 3 of their papers we have counts for
6 papers
Same Cause; Different Effects in the Brain
Mariya Toneva, Jennifer Williams, Anand Bollu +2
To study information processing in the brain, neuroscientists manipulate experimental stimuli while recording participant brain activity. They can then use encoding models to find…
Does injecting linguistic structure into language models lead to better alignment with brain recordings?
Mostafa Abdou, Ana Valeria Gonzalez, Mariya Toneva +2
Neuroscientists evaluate deep neural networks for natural language processing as possible candidate models for how language is processed in the brain. These models are often traine…
Modeling Task Effects on Meaning Representation in the Brain via Zero-Shot MEG Prediction
Mariya Toneva, Otilia Stretcu, Barnabas Poczos +2
How meaning is represented in the brain is still one of the big open questions in neuroscience. Does a word (e.g., bird) always have the same representation, or does the task under…
Inducing brain-relevant bias in natural language processing models
Dan Schwartz, Mariya Toneva, Leila Wehbe
Progress in natural language processing (NLP) models that estimate representations of word sequences has recently been leveraged to improve the understanding of language processing…
Interpreting and improving natural-language processing (in machines) with natural language-processing (in the brain)
Mariya Toneva, Leila Wehbe
Neural networks models for NLP are typically implemented without the explicit encoding of language rules and yet they are able to break one performance record after another. This h…
An Empirical Study of Example Forgetting during Deep Neural Network Learning
Mariya Toneva, Alessandro Sordoni, Remi Tachet des Combes +3
Inspired by the phenomenon of catastrophic forgetting, we investigate the learning dynamics of neural networks as they train on single classification tasks. Our goal is to understa…