4 papers
Wave2Word: A Multimodal Transformer Framework for Joint EEG-Text Alignment and Multi-Task Representation Learning in Neurocritical Care
Argha Kamal Samanta, Deepak Mewada, Monalisa Sarma +1
Continuous electroencephalography (EEG) is routinely used in neurocritical care to monitor seizures and other harmful brain activity, including rhythmic and periodic patterns that…
Clinically Calibrated Machine Learning Benchmarks for Large-Scale Multi-Disorder EEG Classification
Argha Kamal Samanta, Deepak Mewada, Monalisa Sarma +1
Clinical electroencephalography is routinely used to evaluate patients with diverse and often overlapping neurological conditions, yet interpretation remains manual, time-intensive…
Beyond CLIP: Knowledge-Enhanced Multimodal Transformers for Cross-Modal Alignment in Diabetic Retinopathy Diagnosis
Argha Kamal Samanta, Harshika Goyal, Vasudha Joshi +2
Diabetic retinopathy (DR) is a leading cause of preventable blindness worldwide, demanding accurate automated diagnostic systems. While general-domain vision-language models like C…
RADIANT: Retrieval AugmenteD entIty-context AligNmenT -- Introducing RAG-ability and Entity-Context Divergence
Vipula Rawte, Rajarshi Roy, Gurpreet Singh +11
As Large Language Models (LLMs) continue to advance, Retrieval-Augmented Generation (RAG) has emerged as a vital technique to enhance factual accuracy by integrating external knowl…