5 papers
Revealing the Truth with ConLLM for Detecting Multi-Modal Deepfakes
Gautam Siddharth Kashyap, Harsh Joshi, Niharika Jain +4
The rapid rise of deepfake technology poses a severe threat to social and political stability by enabling hyper-realistic synthetic media capable of manipulating public perception.…
Do Clinical Question Answering Systems Really Need Specialised Medical Fine Tuning?
Sushant Kumar Ray, Gautam Siddharth Kashyap, Sahil Tripathi +5
Clinical Question-Answering (CQA) industry systems are increasingly rely on Large Language Models (LLMs), yet their deployment is often guided by the assumption that domain-specifi…
Can We Predict Your Next Move Without Breaking Your Privacy?
Arpita Soni, Sahil Tripathi, Gautam Siddharth Kashyap +5
We propose FLLL3M--Federated Learning with Large Language Models for Mobility Modeling--a privacy-preserving framework for Next-Location Prediction (NxLP). By retaining user data l…
Can We Predict the Unpredictable? Leveraging DisasterNet-LLM for Multimodal Disaster Classification
Manaswi Kulahara, Gautam Siddharth Kashyap, Nipun Joshi +1
Effective disaster management requires timely and accurate insights, yet traditional methods struggle to integrate multimodal data such as images, weather records, and textual repo…
How Can Multimodal Remote Sensing Datasets Transform Classification via SpatialNet-ViT?
Gautam Siddharth Kashyap, Manaswi Kulahara, Nipun Joshi +1
Remote sensing datasets offer significant promise for tackling key classification tasks such as land-use categorization, object presence detection, and rural/urban classification.…