most citedLarge Language Models for Mental Health Diagnostic Assessments: Exploring The Potential of Large Language Models for Assisting with Mental Health Diagnostic Assessments -- The Depression and Anxiety Case

3 citations · 3 across the 2 of their papers we have counts for

collaborators

5 papers

cs.CL2026

VIRAASAT: Traversing Novel Paths for Indian Cultural Reasoning

Harshul Raj Surana, Arijit Maji, Aryan Vats +3

Large Language Models (LLMs) have made significant progress in reasoning tasks across various domains such as mathematics and coding. However, their performance deteriorates in tas…

cs.CV2025

DETONATE: A Benchmark for Text-to-Image Alignment and Kernelized Direct Preference Optimization

Renjith Prasad, Abhilekh Borah, Hasnat Md Abdullah +9

Alignment is crucial for text-to-image (T2I) models to ensure that generated images faithfully capture user intent while maintaining safety and fairness. Direct Preference Optimiza…

cs.CL2025

Chandomitra: Towards Generating Structured Sanskrit Poetry from Natural Language Inputs

Manoj Balaji Jagadeeshan, Samarth Bhatia, Pretam Ray +7

Text Generation has achieved remarkable performance using large language models. It has also been recently well-studied that these large language models are capable of creative gen…

cs.CY2025

NeuroLit Navigator: A Neurosymbolic Approach to Scholarly Article Searches for Systematic Reviews

Vedant Khandelwal, Kaushik Roy, Valerie Lookingbill +4

The introduction of Large Language Models (LLMs) has significantly impacted various fields, including education, for example, by enabling the creation of personalized learning mate…

cs.CL20253 cited

Large Language Models for Mental Health Diagnostic Assessments: Exploring The Potential of Large Language Models for Assisting with Mental Health Diagnostic Assessments -- The Depression and Anxiety Case

Kaushik Roy, Harshul Surana, Darssan Eswaramoorthi +4

Large language models (LLMs) are increasingly attracting the attention of healthcare professionals for their potential to assist in diagnostic assessments, which could alleviate th…