5 papers
MedObvious: Exposing the Medical Moravec's Paradox in VLMs via Clinical Triage
Ufaq Khan, Umair Nawaz, L D M S S Teja +5
Vision Language Models (VLMs) are increasingly used for tasks like medical report generation and visual question answering. However, fluent diagnostic text does not guarantee safe…
AURORA: Adaptive Unified Representation for Robust Ultrasound Analysis
Ufaq Khan, L. D. M. S. Sai Teja, Ayuba Shakiru +4
Ultrasound images vary widely across scanners, operators, and anatomical targets, which often causes models trained in one setting to generalize poorly to new hospitals and clinica…
Disentangling Direction and Magnitude in Transformer Representations: A Double Dissociation Through L2-Matched Perturbation Analysis
Mangadoddi Srikar Vardhan, Lekkala Sai Teja
Transformer hidden states encode information as high-dimensional vectors, yet whether direction (orientation in representational space) and magnitude (vector norm) serve distinct f…
DAMASHA: Detecting AI in Mixed Adversarial Texts via Segmentation with Human-interpretable Attribution
L. D. M. S. Sai Teja, N. Siva Gopala Krishna, Ufaq Khan +2
In the age of advanced large language models (LLMs), the boundaries between human and AI-generated text are becoming increasingly blurred. We address the challenge of segmenting mi…
AGIC: Attention-Guided Image Captioning to Improve Caption Relevance
L. D. M. S. Sai Teja, Ashok Urlana, Pruthwik Mishra
Despite significant progress in image captioning, generating accurate and descriptive captions remains a long-standing challenge. In this study, we propose Attention-Guided Image C…