24 citations · 53 across the 7 of their papers we have counts for
8 papers
The Representational Alignment between Humans and Language Models is implicitly driven by a Concreteness Effect
Cosimo Iaia, Bhavin Choksi, Emily Wiebers +2
The nouns of our language refer to either concrete entities (like a table) or abstract concepts (like justice or love), and cognitive psychology has established that concreteness i…
Limited but consistent gains in adversarial robustness by co-training object recognition models with human EEG
Manshan Guo, Bhavin Choksi, Sari Sadiya +4
In contrast to human vision, artificial neural networks (ANNs) remain relatively susceptible to adversarial attacks. To address this vulnerability, efforts have been made to transf…
Reconstruction of Perceived Images from fMRI Patterns and Semantic Brain Exploration using Instance-Conditioned GANs
Furkan Ozcelik, Bhavin Choksi, Milad Mozafari +2
Reconstructing perceived natural images from fMRI signals is one of the most engaging topics of neural decoding research. Prior studies had success in reconstructing either the low…
Multimodal neural networks better explain multivoxel patterns in the hippocampus
Bhavin Choksi, Milad Mozafari, Rufin VanRullen +1
The human hippocampus possesses "concept cells", neurons that fire when presented with stimuli belonging to a specific concept, regardless of the modality. Recently, similar concep…
On the role of feedback in visual processing: a predictive coding perspective
Andrea Alamia, Milad Mozafari, Bhavin Choksi +1
Brain-inspired machine learning is gaining increasing consideration, particularly in computer vision. Several studies investigated the inclusion of top-down feedback connections in…
Predify: Augmenting deep neural networks with brain-inspired predictive coding dynamics
Bhavin Choksi, Milad Mozafari, Callum Biggs O'May +3
Deep neural networks excel at image classification, but their performance is far less robust to input perturbations than human perception. In this work we explore whether this shor…
Does language help generalization in vision models?
Benjamin Devillers, Bhavin Choksi, Romain Bielawski +1
Vision models trained on multimodal datasets can benefit from the wide availability of large image-caption datasets. A recent model (CLIP) was found to generalize well in zero-shot…
Predictive coding feedback results in perceived illusory contours in a recurrent neural network
Zhaoyang Pang, Callum Biggs O'May, Bhavin Choksi +1
Modern feedforward convolutional neural networks (CNNs) can now solve some computer vision tasks at super-human levels. However, these networks only roughly mimic human visual perc…