collaborators

7 papers

cs.CV2026

MapRoute++: Surrogate-Guided Semantic Routing for Visual Concept Unlearning

Ashok Urlana, L. D. M. S. Sai Teja, Vivek Hruday Kavuri +1

We present our submission to Task 3 of the Gen 2.0 Challenge on visual concept unlearning. Building on MapRoute, we introduce task-specific training objectives, richer concept r…

cs.CL2026

PolyAlign: Conditional Human-Distribution Alignment

L. D. M. S. Sai Teja, Ufaq Khan, Sathira Silva +2

Post-training methods such as supervised fine-tuning (SFT) and preference optimization typically align language models toward a single global assistant behavior. While effective fo…

cs.CV2026

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…

cs.CV2026

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…

cs.CL2026

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…

cs.CL2026

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…