Muhammad Huzaifa — accepted AI-conference papers

2026

VisualOverload: Probing Visual Understanding of VLMs in Really Dense Scenes

Paul Gavrikov, Wei Lin, M. Jehanzeb Mirza, Soumya Jahagirdar, Muhammad Huzaifa, Sivan Doveh +3

CVPR 2026

Is basic visual understanding really solved in state-of-the-art VLMs? We present VisualOverload, a slightly different visual question answering (VQA) benchmark comprising 2,720 question-answer pairs, with privately held ground-truth responses. Unlike prior VQA datasets that typically focus on near g

Cited by 0 Source ↗code ↗Scholar ↗

2022

On-Device CPU Scheduling for Robot Systems

Aditi Partap, Samuel Grayson, Muhammad Huzaifa, Sarita Adve, Brighten Godfrey, Saurabh Gupta +2

IROS 2022poster

Robots have to take highly responsive real-time actions, driven by complex decisions involving a pipeline of sensing, perception, planning, and reaction tasks. These tasks must be scheduled on resource-constrained devices such that the performance goals and the requirements of the application are me…

Cited by 5 Source ↗Scholar ↗