Papers by Raju S. Bapi

2 papers
Visio-Linguistic Brain Encoding (2022.coling-1)

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Challenge: Existing studies have failed to explore co-attentive multi-modal modeling for visual and text reasoning.
Approach: They propose to use image and multi-modal Transformers to reconstruct fMRI brain activity . they use two popular datasets to study visual and text reasoning .
Outcome: The proposed model outperforms existing models on two popular datasets . the results raise the question whether visual processing is affected implicitly by linguistic processing .
Multi-view and Cross-view Brain Decoding (2022.coling-1)

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Challenge: a recent study has shown that brain decoding models can decode concepts from single view . a multi-view decoder can take brain recordings for any view as input and predict the concept .
Approach: They propose to build a multi-view decoder that can take brain recordings for any view as input and predict the concept.
Outcome: The proposed systems can decode concepts from brain recordings from any view . the proposed systems have 0.68 pairwise accuracy across view pairs and 0.8 average pairwise precision across tasks.

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