activity
20242026
collaborators

7 papers

cs.CL2026

OMIND: Framework for Knowledge Grounded Finetuning and Multi-Turn Dialogue Benchmark for Mental Health LLMs

Suraj Racha, Prashant Harish Joshi, Utkarsh Maurya +6

Large Language Models (LLMs) have shown remarkable capabilities for complex tasks, yet adaptation in medical domain, specifically mental health, poses specific challenges. Mental h…

cs.CL2025

BhashaBench V1: A Comprehensive Benchmark for the Quadrant of Indic Domains

Vijay Devane, Mohd Nauman, Bhargav Patel +14

The rapid advancement of large language models(LLMs) has intensified the need for domain and culture specific evaluation. Existing benchmarks are largely Anglocentric and domain-ag…

cs.CL2025

PARAM-1 BharatGen 2.9B Model

Kundeshwar Pundalik, Piyush Sawarkar, Nihar Sahoo +19

Large Language Models (LLMs) have emerged as powerful general-purpose reasoning systems, yet their development remains dominated by English-centric data, architectures, and optimiz…

cs.AI2025

Inducing Robustness in a 2 Dimensional Direct Preference Optimization Paradigm

Sarvesh Shashidhar, Ritik, Nachiketa Patil +2

Direct Preference Optimisation (DPO) has emerged as a powerful method for aligning Large Language Models (LLMs) with human preferences, offering a stable and efficient alternative…

cs.LG2025

INDIC QA BENCHMARK: A Multilingual Benchmark to Evaluate Question Answering capability of LLMs for Indic Languages

Abhishek Kumar Singh, Vishwajeet kumar, Rudra Murthy +3

Large Language Models (LLMs) perform well on unseen tasks in English, but their abilities in non English languages are less explored due to limited benchmarks and training data. To…

cs.CL2025

MHQA: A Diverse, Knowledge Intensive Mental Health Question Answering Challenge for Language Models

Suraj Racha, Prashant Joshi, Anshika Raman +4

Mental health remains a challenging problem all over the world, with issues like depression, anxiety becoming increasingly common. Large Language Models (LLMs) have seen a vast app…