most citedWho is Responsible? The Data, Models, Users or Regulations? A Comprehensive Survey on Responsible Generative AI for a Sustainable Future

5 citations · 8 across the 14 of their papers we have counts for

collaborators

16 papers

cs.CV2026

Geometric Parrots: Rule Absence vs. Rule Fragility in Spatial and Physical Reasoning for Vision-Language Models

Bilal Jawaid, Hamza Hanif, Muhammad Maaz Uddin +8

Vision-language models (VLMs) can answer many geometric and physical reasoning questions correctly, yet still behave inconsistently in interaction, for example, abandoning a correc…

cs.CL2026

Efficient RAG with Intent-Aware Retrieval and Semantics-Preserving Chunking

Fachrina Dewi Puspitasari, Chaoning Zhang, Jiaquan Zhang +6

The demand for powerful instruction following and reasoning capability of large language models (LLMs) has promoted rapid development of retrieval-augmented generation (RAG). The R…

cs.CV2026

Towards Responsible Multimodal Medical Reasoning via Context-Aligned Vision-Language Models

Sumra Khan, Sagar Chhabriya, Aizan Zafar +5

Medical vision-language models (VLMs) show strong performance on radiology tasks but often produce fluent yet weakly grounded conclusions due to over-reliance on a dominant modalit…

cs.LG2026

Scaling Laws in the Tiny Regime: How Small Models Change Their Mistakes

Mohammed Alnemari, Rizwan Qureshi, Nader Begrazadah

Neural scaling laws describe how model performance improves as a power law with size, but existing work focuses on models above 100M parameters. The sub-20M regime -- where TinyML…

cs.CV2026

Beyond Anatomy: Explainable ASD Classification from rs-fMRI via Functional Parcellation and Graph Attention Networks

Syeda Hareem Madani, Noureen Bibi, Adam Rafiq Jeraj +3

Anatomical brain parcellations dominate rs-fMRI-based Autism Spectrum Disorder (ASD) classification, yet their rigid boundaries may fail to capture the idiosyncratic connectivity p…

cs.CL2025

Prompting Away Stereotypes? Evaluating Bias in Text-to-Image Models for Occupations

Shaina Raza, Maximus Powers, Partha Pratim Saha +2

Text-to-Image (TTI) models are powerful creative tools but risk amplifying harmful social biases. We frame representational societal bias assessment as an image curation and evalua…

cs.CV2025

Calibrated and Robust Foundation Models for Vision-Language and Medical Image Tasks Under Distribution Shift

Behraj Khan, Tahir Qasim Syed, Nouman M. Durrani +3

Foundation models like CLIP and SAM have advanced computer vision and medical imaging via low-shot transfer learning, aiding CADD with limited data. However, their deployment faces…

cs.AI2025★ 1 cited

Thinking Beyond Tokens: From Brain-Inspired Intelligence to Cognitive Foundations for Artificial General Intelligence and its Societal Impact

Rizwan Qureshi, Ranjan Sapkota, Abbas Shah +16

Can machines truly think, reason and act in domains like humans? This enduring question continues to shape the pursuit of Artificial General Intelligence (AGI). Despite the growing…

cs.CV2025★ 2 cited

Leveraging MIMIC Datasets for Better Digital Health: A Review on Open Problems, Progress Highlights, and Future Promises

Afifa Khaled, Mohammed Sabir, Rizwan Qureshi +4

The Medical Information Mart for Intensive Care (MIMIC) datasets have become the Kernel of Digital Health Research by providing freely accessible, deidentified records from tens of…

cs.CV2025

A Layered Self-Supervised Knowledge Distillation Framework for Efficient Multimodal Learning on the Edge

Tarique Dahri, Zulfiqar Ali Memon, Zhenyu Yu +6

We introduce Layered Self-Supervised Knowledge Distillation (LSSKD) framework for training compact deep learning models. Unlike traditional methods that rely on pre-trained teacher…

cs.CV2025

SatelliteFormula: Multi-Modal Symbolic Regression from Remote Sensing Imagery for Physics Discovery

Zhenyu Yu, Mohd. Yamani Idna Idris, Pei Wang +3

We propose SatelliteFormula, a novel symbolic regression framework that derives physically interpretable expressions directly from multi-spectral remote sensing imagery. Unlike tra…

cs.CL2025

Just as Humans Need Vaccines, So Do Models: Model Immunization to Combat Falsehoods

Shaina Raza, Rizwan Qureshi, Azib Farooq +4

Large language models (LLMs) reproduce misinformation not by memorizing false facts alone, but by learning the linguistic patterns that make falsehoods persuasive, such as hedging,…

cs.CV2025

DanceText: A Training-Free Layered Framework for Controllable Multilingual Text Transformation in Images

Zhenyu Yu, Mohd Yamani Idna Idris, Hua Wang +6

We present DanceText, a training-free framework for multilingual text editing in images, designed to support complex geometric transformations and achieve seamless foreground-backg…

cs.CL2025

VLDBench Evaluating Multimodal Disinformation with Regulatory Alignment

Shaina Raza, Ashmal Vayani, Aditya Jain +8

Detecting disinformation that blends manipulated text and images has become increasingly challenging, as AI tools make synthetic content easy to generate and disseminate. While mos…

cs.CY2025★ 5 cited

Who is Responsible? The Data, Models, Users or Regulations? A Comprehensive Survey on Responsible Generative AI for a Sustainable Future

Shaina Raza, Rizwan Qureshi, Anam Zahid +14

Generative AI is rapidly moving from research to deployment, elevating the need for responsible development, evaluation, and governance. We conduct a PRISMA guided review of 232 st…

cs.CV2025

Confidence-calibrated covariate shift correction for few-shot classification in Vision-Language Models

Behraj Khan, Rizwan Qureshi, Nouman Muhammad Durrani +1

Since the establishment of vision-language foundation models as the new mainstay in low-shot vision classification tasks, the question of domain generalization arising from insuffi…