Subhadip Baidya — accepted AI-conference papers

2026

ArogyaSutra: A Multi-Agent Framework for Multimodal Medical Reasoning in Indic Languages

Tanmoy Halder, Akash Ghosh, Subhadip Baidya, Arijit Roy, Sriparna Saha

IJCAI 2026

Multimodal Large Language Models(MLLMs) have shown promising reasoning capabilities in general domains, yet their performance remains limited in specialized settings such as healthcare, particularly for multilingual and low-resource scenarios. This gap is critical in regions like rural India, where

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2025

RELIC: Enhancing Reward Model Generalization for Low-Resource Indic Languages with Few-Shot Examples

Soumya Suvra Ghosal, Vaibhav Singh, Akash Ghosh, Soumyabrata Pal, Subhadip Baidya, Sriparna Saha +1

EMNLP 2025

Reward models are essential for aligning large language models (LLMs) with human preferences. However, most open-source multilingual reward models are primarily trained on preference datasets in high-resource languages, resulting in unreliable reward signals for low-resource Indic languages. Collect

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