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20162026
most citedDepressionNet: A Novel Summarization Boosted Deep Framework for Depression Detection on Social Media

80 citations · 311 across the 38 of their papers we have counts for

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Showing 2026Show all

6 papers · 1 filter

cs.CV2026

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…

cs.CV2026

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…

eess.IV2026

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…

cs.IR2026

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…

cs.IR2026

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…

cs.CL2026

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…