6 papers
Attacking Graph Foundation Models Through Their Shared Representation
Pankaj Kumar, Subhankar Mishra
A graph foundation model generalizes across graph domains by mapping every input into one shared representation before any task reasoning. We call this map the alignment layer, the…
OpenProposal Platform for Transparent Research Funding Review
Sakshi Ahuja, Subhankar Mishra
Research funding allocation remains a critical bottleneck in scientific advancement, yet the review process for funding proposals lacks the transparency that has revolutionized aca…
QGShap: Quantum Acceleration for Faithful GNN Explanations
Haribandhu Jena, Jyotirmaya Shivottam, Subhankar Mishra
Graph Neural Networks (GNNs) have become indispensable in critical domains such as drug discovery, social network analysis, and recommendation systems, yet their black-box nature h…
Robustness in Large Language Models: A Survey of Mitigation Strategies and Evaluation Metrics
Pankaj Kumar, Subhankar Mishra
Large Language Models (LLMs) have emerged as a promising cornerstone for the development of natural language processing (NLP) and artificial intelligence (AI). However, ensuring th…
QGraphLIME - Explaining Quantum Graph Neural Networks
Haribandhu Jena, Jyotirmaya Shivottam, Subhankar Mishra
Quantum graph neural networks offer a powerful paradigm for learning on graph-structured data, yet their explainability is complicated by measurement-induced stochasticity and the…
Retinal Fundus Multi-Disease Image Classification using Hybrid CNN-Transformer-Ensemble Architectures
Deependra Singh, Saksham Agarwal, Subhankar Mishra
Our research is motivated by the urgent global issue of a large population affected by retinal diseases, which are evenly distributed but underserved by specialized medical experti…