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Asif Hanif

Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI)

7 papers hereh-index 337 citations11 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • first author3
  • middle author4

Across the 7 of 7 papers where every author was matched, so the position is known.

fields
  • cs.CV4
  • cs.SD2
  • eess.IV1
affiliations
  • Mohamed Bin Zayed University of Artificial Intelligence (MBZUAI)
HomepageORCID 0000-0002-6705-149X
same name
  • Asif Hanif — 4 papers, h 25

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20242026
collaborators
Showing cs.CVShow all

4 papers · 1 filter

cs.CV2026

Lost in Volume: The CT-SpatialVQA Benchmark for Evaluating Semantic-Spatial Understanding of 3D Medical Vision-Language Models

Mashrafi Monon, Umaima Rahman, Asif Hanif +2

Recent advances in 3D medical vision-language models have enabled joint reasoning over volumetric images and text, showing strong performance in medical visual question-answering (…

cs.CV2026

DARK: Diagonal-Anchored Repulsive Knowledge Distillation for Vision-Language Models under Extreme Compression

Numan Saeed, Asif Hanif, Fadillah Adamsyah Maani +2

Compressing vision-language models for on-device deployment is increasingly important in clinical settings, but knowledge distillation (KD) degrades sharply when the teacher-studen…

cs.CV2025

Noise is an Efficient Learner for Zero-Shot Vision-Language Models

Raza Imam, Asif Hanif, Jian Zhang +3

Recently, test-time adaptation has garnered attention as a method for tuning models without labeled data. The conventional modus operandi for adapting pre-trained vision-language m…

cs.CV2024

BAPLe: Backdoor Attacks on Medical Foundational Models using Prompt Learning

Asif Hanif, Fahad Shamshad, Muhammad Awais +5

Medical foundation models are gaining prominence in the medical community for their ability to derive general representations from extensive collections of medical image-text pairs…

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