24 citations · 46 across the 11 of their papers we have counts for
11 papers
Task-conditioned probing of instruction-tuned multimodal LLMs: Region-specific brain alignment patterns under naturalistic stimuli
Subba Reddy Oota, Khushbu Pahwa, Prachi Jindal +5
Recent voxel-wise multimodal brain encoding studies have shown that multimodal large language models (MLLMs) exhibit a higher degree of brain alignment compared to unimodal models.…
Correlating instruction-tuning (in multimodal models) with vision-language processing (in the brain)
Subba Reddy Oota, Akshett Jindal, Ishani Mondal +6
Transformer-based language models, though not explicitly trained to mimic brain recordings, have demonstrated surprising alignment with brain activity. Progress in these models-thr…
Multi-modal brain encoding models for multi-modal stimuli
Subba Reddy Oota, Khushbu Pahwa, Mounika Marreddy +3
Despite participants engaging in unimodal stimuli, such as watching images or silent videos, recent work has demonstrated that multi-modal Transformer models can predict visual bra…
IndicSentEval: How Effectively do Multilingual Transformer Models encode Linguistic Properties for Indic Languages?
Akhilesh Aravapalli, Mounika Marreddy, Radhika Mamidi +2
Transformer-based models have revolutionized the field of natural language processing. To understand why they perform so well and to assess their reliability, several studies have…
USDC: A Dataset of ser tance and ogmatism in Long onversations
Mounika Marreddy, Subba Reddy Oota, Venkata Charan Chinni +2
Analyzing user opinion changes in long conversation threads is extremely critical for applications like enhanced personalization, market research, political campaigns, customer ser…
Deep Neural Networks and Brain Alignment: Brain Encoding and Decoding (Survey)
Subba Reddy Oota, Zijiao Chen, Manish Gupta +4
Can artificial intelligence unlock the secrets of the human brain? How do the inner mechanisms of deep learning models relate to our neural circuits? Is it possible to enhance AI b…
On Robustness of Finetuned Transformer-based NLP Models
Pavan Kalyan Reddy Neerudu, Subba Reddy Oota, Mounika Marreddy +2
Transformer-based pretrained models like BERT, GPT-2 and T5 have been finetuned for a large number of natural language processing (NLP) tasks, and have been shown to be very effect…
Syntactic Structure Processing in the Brain while Listening
Subba Reddy Oota, Mounika Marreddy, Manish Gupta +1
Syntactic parsing is the task of assigning a syntactic structure to a sentence. There are two popular syntactic parsing methods: constituency and dependency parsing. Recent works h…
Joint processing of linguistic properties in brains and language models
Subba Reddy Oota, Manish Gupta, Mariya Toneva
Language models have been shown to be very effective in predicting brain recordings of subjects experiencing complex language stimuli. For a deeper understanding of this alignment,…
Neural Language Taskonomy: Which NLP Tasks are the most Predictive of fMRI Brain Activity?
Subba Reddy Oota, Jashn Arora, Veeral Agarwal +3
Several popular Transformer based language models have been found to be successful for text-driven brain encoding. However, existing literature leverages only pretrained text Trans…
Cross-view Brain Decoding
Subba Reddy Oota, Jashn Arora, Manish Gupta +1
How the brain captures the meaning of linguistic stimuli across multiple views is still a critical open question in neuroscience. Consider three different views of the concept apar…