80 citations · 311 across the 38 of their papers we have counts for
40 papers
Causal-RetiGraph: Cross-Cohort Retinal Support and Same-Subject Pathway Analysis for Diabetic Retinopathy
Inam Ullah, Imran Razzak, Shoaib Jameel
Diabetic retinopathy (DR) is a local retinal lesion process and a visible manifestation of systemic microvascular injury. Modern retinal AI can grade images accurately, but often l…
RetiSEM: Generalising Causal Models for Fragmented Biomedical Data
Inam Ullah, Imran Razzak, Shoaib Jameel
Learning causal models from fragmented biomedical data is challenging because clinical, molecular, and imaging variables are often incomplete or not jointly observed. We propose Re…
A Dual Edge Spatial Jacobian Image Graph for Interpretable Diabetic Retinopathy Grading
Inam Ullah, Imran Razzak, Shoaib Jameel
Automated diabetic retinopathy (DR) grading from colour fundus photographs can achieve strong predictive performance, but clinical interpretation requires more than an image-level…
Knowledge Graph Enhanced Memory-Augmented Retrieval for Long Context Modeling
Ghadir Alselwi, Basem Suleiman, Hao Xue +4
Long-context language modeling requires not only extending context windows but maintaining coherent understanding of entity states and relationships across thousands of tokens -- a…
Mitigating Preference Leakage via Strict Estimator Separation for Normative Generative Ranking
Dalia Nahhas, Xiaohao Cai, Imran Razzak +1
In Generative Information Retrieval (GenIR), the bottleneck has shifted from generation to the selection of candidates, particularly for normative criteria such as cultural relevan…
CALM: Culturally Self-Aware Language Models
Lingzhi Shen, Xiaohao Cai, Yunfei Long +3
Cultural awareness in language models is the capacity to understand and adapt to diverse cultural contexts. However, most existing approaches treat culture as static background kno…
HIPPD: Brain-Inspired Hierarchical Information Processing for Personality Detection
Guanming Chen, Lingzhi Shen, Xiaohao Cai +2
Personality detection from text aims to infer an individual's personality traits based on linguistic patterns. However, existing machine learning approaches often struggle to captu…
HeSRN: Representation Learning On Heterogeneous Graphs via Slot-Aware Retentive Network
Yifan Lu, Ziyun Zou, Belal Alsinglawi +6
Graph Transformers have recently achieved remarkable progress in graph representation learning by capturing long-range dependencies through self-attention. However, their quadratic…
EmoPerso: Enhancing Personality Detection with Self-Supervised Emotion-Aware Modelling
Lingzhi Shen, Xiaohao Cai, Yunfei Long +3
Personality detection from text is commonly performed by analysing users' social media posts. However, existing methods heavily rely on large-scale annotated datasets, making it ch…
Retinal Lipidomics Associations as Candidate Biomarkers for Cardiovascular Health
Inamullah, Imran Razzak, Shoaib Jameel
Retinal microvascular imaging is increasingly recognised as a non invasive method for evaluating systemic vascular and metabolic health. However, the association between lipidomics…
Integrated Oculomics and Lipidomics Reveal Microvascular Metabolic Signatures Associated with Cardiovascular Health in a Healthy Cohort
Inamullah, Ernesto Elias Vidal Rosas, Imran Razzak +1
Cardiovascular disease (CVD) remains the leading global cause of mortality, yet current risk stratification methods often fail to detect early, subclinical changes. Previous studie…
Flick: Few Labels Text Classification using K-Aware Intermediate Learning in Multi-Task Low-Resource Languages
Ali Almutairi, Abdullah Alsuhaibani, Shoaib Jameel +3
Training deep learning networks with minimal supervision has gained significant research attention due to its potential to reduce reliance on extensive labelled data. While self-tr…
DeepChest: Dynamic Gradient-Free Task Weighting for Effective Multi-Task Learning in Chest X-ray Classification
Youssef Mohamed, Noran Mohamed, Khaled Abouhashad +5
While Multi-Task Learning (MTL) offers inherent advantages in complex domains such as medical imaging by enabling shared representation learning, effectively balancing task contrib…
TAGS: A Test-Time Generalist-Specialist Framework with Retrieval-Augmented Reasoning and Verification
Jianghao Wu, Feilong Tang, Yulong Li +5
Recent advances such as Chain-of-Thought prompting have significantly improved large language models (LLMs) in zero-shot medical reasoning. However, prompting-based methods often r…
The Eye as a Window to Systemic Health: A Survey of Retinal Imaging from Classical Techniques to Oculomics
Inamullah, Imran Razzak, Shoaib Jameel
The unique vascularized anatomy of the human eye, encased in the retina, provides an opportunity to act as a window for human health. The retinal structure assists in assessing the…
Less but Better: Parameter-Efficient Fine-Tuning of Large Language Models for Personality Detection
Lingzhi Shen, Yunfei Long, Xiaohao Cai +3
Personality detection automatically identifies an individual's personality from various data sources, such as social media texts. However, as the parameter scale of language models…
LL4G: Self-Supervised Dynamic Optimization for Graph-Based Personality Detection
Lingzhi Shen, Yunfei Long, Xiaohao Cai +4
Graph-based personality detection constructs graph structures from textual data, particularly social media posts. Current methods often struggle with sparse or noisy data and rely…
Enforcing Consistency and Fairness in Multi-level Hierarchical Classification with a Mask-based Output Layer
Shijing Chen, Shoaib Jameel, Mohamed Reda Bouadjenek +6
Traditional Multi-level Hierarchical Classification (MLHC) classifiers often rely on backbone models with independent output layers. This structure tends to overlook the hierar…
Long Context Modeling with Ranked Memory-Augmented Retrieval
Ghadir Alselwi, Hao Xue, Shoaib Jameel +3
Effective long-term memory management is crucial for language models handling extended contexts. We introduce the Enhanced Ranked Memory Augmented Retrieval (ERMAR) framework, whic…
Leveraging Taxonomy and LLMs for Improved Multimodal Hierarchical Classification
Shijing Chen, Mohamed Reda Bouadjenek, Shoaib Jameel +5
Multi-level Hierarchical Classification (MLHC) tackles the challenge of categorizing items within a complex, multi-layered class structure. However, traditional MLHC classifiers of…
Modeling Multi-modal Cross-interaction for Multi-label Few-shot Image Classification Based on Local Feature Selection
Kun Yan, Zied Bouraoui, Fangyun Wei +4
The aim of multi-label few-shot image classification (ML-FSIC) is to assign semantic labels to images, in settings where only a small number of training examples are available for…
GAMED: Knowledge Adaptive Multi-Experts Decoupling for Multimodal Fake News Detection
Lingzhi Shen, Yunfei Long, Xiaohao Cai +4
Multimodal fake news detection often involves modelling heterogeneous data sources, such as vision and language. Existing detection methods typically rely on fusion effectiveness a…
NarrationDep: Narratives on Social Media For Automatic Depression Detection
Hamad Zogan, Imran Razzak, Shoaib Jameel +1
Social media posts provide valuable insight into the narrative of users and their intentions, including providing an opportunity to automatically model whether a social media user…
BayesJudge: Bayesian Kernel Language Modelling with Confidence Uncertainty in Legal Judgment Prediction
Ubaid Azam, Imran Razzak, Shelly Vishwakarma +3
Predicting legal judgments with reliable confidence is paramount for responsible legal AI applications. While transformer-based deep neural networks (DNNs) like BERT have demonstra…