activity
20222026
most citedMedViT: A Robust Vision Transformer for Generalized Medical Image Classification

495 citations · 564 across the 13 of their papers we have counts for

collaborators

13 papers

cs.CV2026

Recursive Vision Language Models for General Symbolic Reasoning

Omid Nejati Manzari, Guillaume Lajoie, Hassan Rivaz

Hard symbolic-reasoning tasks such as Sudoku, maze pathfinding, and ARC remain challenging for LLMs due to their fixed-depth autoregressive reasoning, which limits systematic searc…

cs.CV2026

Sparse Spectral LoRA: Routed Experts for Medical VLMs

Omid Nejati Manzari, Hojat Asgariandehkordi, Taha Koleilat +2

Large vision-language models (VLMs) excel on general benchmarks but often lack robustness in medical imaging, where heterogeneous supervision induces cross-dataset interference and…

cs.CV2026

MedCLIPSeg: Probabilistic Vision-Language Adaptation for Data-Efficient and Generalizable Medical Image Segmentation

Taha Koleilat, Hojat Asgariandehkordi, Omid Nejati Manzari +3

Medical image segmentation remains challenging due to limited annotations for training, ambiguous anatomical features, and domain shifts. While vision-language models such as CLIP…

cs.CV2025★ 6 cited

Med-VCD: Mitigating Hallucination for Medical Large Vision Language Models through Visual Contrastive Decoding

Zahra Mahdavi, Zahra Khodakaramimaghsoud, Hooman Khaloo +4

Large vision-language models (LVLMs) are now central to healthcare applications such as medical visual question answering and imaging report generation. Yet, these models remain vu…

cs.CV2025

Enhancing Vehicle Make and Model Recognition with 3D Attention Modules

Narges Semiromizadeh, Omid Nejati Manzari, Shahriar B. Shokouhi +1

Vehicle make and model recognition (VMMR) is a crucial component of the Intelligent Transport System, garnering significant attention in recent years. VMMR has been widely utilized…

cs.CV2025★ 34 cited

Medical Image Classification with KAN-Integrated Transformers and Dilated Neighborhood Attention

Omid Nejati Manzari, Hojat Asgariandehkordi, Taha Koleilat +2

Convolutional networks, transformers, hybrid models, and Mamba-based architectures have demonstrated strong performance across various medical image classification tasks. However,…