2 citations · 2 across the 6 of their papers we have counts for
6 papers
LAMP: Learning Universal Adversarial Perturbations for Multi-Image Tasks via Pre-trained Models
Alvi Md Ishmam, Najibul Haque Sarker, Zaber Ibn Abdul Hakim +1
Multimodal Large Language Models (MLLMs) have achieved remarkable performance across vision-language tasks. Recent advancements allow these models to process multiple images as inp…
SoundBreak: A Systematic Study of Audio-Only Adversarial Attacks on Trimodal Models
Aafiya Hussain, Gaurav Srivastava, Alvi Ishmam +2
Multimodal foundation models that integrate audio, vision, and language achieve strong performance on reasoning and generation tasks, yet their robustness to adversarial manipulati…
Semantic Shield: Defending Vision-Language Models Against Backdooring and Poisoning via Fine-grained Knowledge Alignment
Alvi Md Ishmam, Christopher Thomas
In recent years there has been enormous interest in vision-language models trained using self-supervised objectives. However, the use of large-scale datasets scraped from the web f…
JourneyBench: A Challenging One-Stop Vision-Language Understanding Benchmark of Generated Images
Zhecan Wang, Junzhang Liu, Chia-Wei Tang +11
Existing vision-language understanding benchmarks largely consist of images of objects in their usual contexts. As a consequence, recent multimodal large language models can perfor…
Towards Interpretable Multilingual Detection of Hate Speech against Immigrants and Women in Twitter at SemEval-2019 Task 5
Alvi Md Ishmam
his paper describes our techniques to detect hate speech against women and immigrants on Twitter in multilingual contexts, particularly in English and Spanish. The challenge was de…
Challenges of Bridging the Gap between Mass People and Welfare Organizations in Bangladesh
Alvi Md Ishmam, Md Raihan Mia
Computing for the development of marginalized communities is a big deal of challenges for researchers. Different social organizations are working to develop the conditions of a spe…