189 citations · 205 across the 8 of their papers we have counts for
9 papers
On Diophantine tuples involving star numbers
Tapas Chatterjee, Sagar Mandal
In this paper, we discuss two related Diophantine tuple problems involving star numbers . First, we investigate classical -tuples whose elements are star numbe…
IndicFairFace: Balanced Indian Face Dataset for Auditing and Mitigating Geographical Bias in Vision-Language Models
Aarish Shah Mohsin, Mohammed Tayyab Ilyas Khan, Mohammad Nadeem +3
Vision-Language Models (VLMs) are known to inherit and amplify societal biases from their web-scale training data with Indian being particularly misrepresented. Existing fairness-a…
Surgeons Are Indian Males and Speech Therapists Are White Females: Auditing Biases in Vision-Language Models for Healthcare Professionals
Zohaib Hasan Siddiqui, Dayam Nadeem, Mohammad Masudur Rahman +3
Vision language models (VLMs), such as CLIP and OpenCLIP, can encode and reflect stereotypical associations between medical professions and demographic attributes learned from web-…
Beyond Specialization: Benchmarking LLMs for Transliteration of Indian Languages
Gulfarogh Azam, Mohd Sadique, Saif Ali +4
Transliteration, the process of mapping text from one script to another, plays a crucial role in multilingual natural language processing, especially within linguistically diverse…
Gender Bias in Text-to-Video Generation Models: A case study of Sora
Mohammad Nadeem, Shahab Saquib Sohail, Erik Cambria +2
The advent of text-to-video generation models has revolutionized content creation as it produces high-quality videos from textual prompts. However, concerns regarding inherent bias…
Owls are wise and foxes are unfaithful: Uncovering animal stereotypes in vision-language models
Tabinda Aman, Mohammad Nadeem, Shahab Saquib Sohail +2
Animal stereotypes are deeply embedded in human culture and language. They often shape our perceptions and expectations of various species. Our study investigates how animal stereo…
Negation Blindness in Large Language Models: Unveiling the NO Syndrome in Image Generation
Mohammad Nadeem, Shahab Saquib Sohail, Erik Cambria +2
Foundational Large Language Models (LLMs) have changed the way we perceive technology. They have been shown to excel in tasks ranging from poem writing and coding to essay generati…
Decoding ChatGPT: A Taxonomy of Existing Research, Current Challenges, and Possible Future Directions
Shahab Saquib Sohail, Faiza Farhat, Yassine Himeur +5
Chat Generative Pre-trained Transformer (ChatGPT) has gained significant interest and attention since its launch in November 2022. It has shown impressive performance in various do…
Filter Bubbles in Recommender Systems: Fact or Fallacy -- A Systematic Review
Qazi Mohammad Areeb, Mohammad Nadeem, Shahab Saquib Sohail +5
A filter bubble refers to the phenomenon where Internet customization effectively isolates individuals from diverse opinions or materials, resulting in their exposure to only a sel…