activity
20242026
collaborators

10 papers

q-bio.NC2026

Brain alignment of reasoning and action representations from vision-language and action models during naturalistic gameplay

Subba Reddy Oota, Anant Khandelwal, Khushbu Pahwa +4

Understanding how humans and artificial intelligence systems predict and plan by interacting with their environment is a fundamental challenge at the intersection of neuroscience a…

q-bio.NC2026

How does longer temporal context enhance multimodal narrative video processing in the brain?

Prachi Jindal, Anant Khandelwal, Manish Gupta +3

Understanding how humans and artificial intelligence systems process complex narrative videos is a fundamental challenge at the intersection of neuroscience and machine learning. T…

q-bio.NC2026

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.…

cs.CV2026

A Deep Multi-Modal Method for Patient Wound Healing Assessment

Subba Reddy Oota, Vijay Rowtula, Shahid Mohammed +3

Hospitalization of patients is one of the major factors for high wound care costs. Most patients do not acquire a wound which needs immediate hospitalization. However, due to facto…

q-bio.NC2026

Linguistic properties and model scale in brain encoding: from small to compressed language models

Subba Reddy Oota, Vijay Rowtula, Satya Sai Srinath Namburi +5

Recent work has shown that scaling large language models (LLMs) improves their alignment with human brain activity, yet it remains unclear what drives these gains and which represe…

cs.CL2025

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…