80 citations · 228 across the 103 of their papers we have counts for
109 papers
BARRAC: Adaptation of an English Aspect-based Sentiment Analysis Approach for Classification Tasks in Arabic Dialects
Ali Almutairi, Gelareh Mohammadi, Imran Razzak +1
With the rapid growth of Arabic NLP, several models, datasets and benchmarks have been reported. This paper asks whether approaches developed for majority languages like English ca…
TopoBrick: Agentic Topology Sampling of Exogenous Variables for Zero-Shot Building IoT Forecasting
Xiachong Lin, Du Yin, Arian Prabowo +6
Building sensors are embedded in physical topology, spatial hierarchy, and operational context, yet existing forecasters often treat them as isolated time series or rely on fixed c…
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…
PRISM: A Personality-Driven Multi-Agent Framework for Social Media Simulation
Zhixiang Lu, Xueyuan Deng, Yiran Liu +4
Traditional agent-based models (ABMs) of opinion dynamics often fail to capture the psychological heterogeneity driving online polarization due to simplistic homogeneity assumption…
SelfAI: A self-directed framework for long-horizon scientific discovery
Xiao Wu, Ting-Zhu Huang, Liang-Jian Deng +9
Scientific discovery increasingly entails long-horizon exploration of complex hypothesis spaces, yet most existing approaches emphasize final performance while offering limited ins…
QuAnTS: Question Answering on Time Series
Felix Divo, Maurice Kraus, Anh Q. Nguyen +5
Text offers intuitive access to information. This can, in particular, complement the density of numerical time series, thereby enabling improved interactions with time series model…
CHIPS: Efficient CLIP Adaptation via Curvature-aware Hybrid Influence-based Data Selection
Xinlin Zhuang, Yichen Li, Xiwei Liu +11
Adapting CLIP to vertical domains is typically approached by novel fine-tuning strategies or by continual pre-training (CPT) on large domain-specific datasets. Yet, data itself rem…
Robust Atypical Mitosis Classification with DenseNet121: Stain-Aware Augmentation and Hybrid Loss for Domain Generalization
Adinath Dukre, Ankan Deria, Yutong Xie +1
Atypical mitotic figures are important biomarkers of tumor aggressiveness in histopathology, yet reliable recognition remains challenging due to severe class imbalance and variabil…
Electric Vehicle Charging Load Modeling: A Survey, Trends, Challenges and Opportunities
Xiachong Lin, Arian Prabowo, Imran Razzak +4
The evolution of electric vehicles (EVs) is reshaping the automotive industry, advocating for more sustainable transportation practices. Accurately predicting EV charging behavior…
Phenome-Wide Multi-Omics Integration Uncovers Distinct Archetypes of Human Aging
Huifa Li, Feilong Tang, Haochen Xue +5
Aging is a highly complex and heterogeneous process that progresses at different rates across individuals, making biological age (BA) a more accurate indicator of physiological dec…
Few-Label Multimodal Modeling of SNP Variants and ECG Phenotypes Using Large Language Models for Cardiovascular Risk Stratification
Niranjana Arun Menon, Yulong Li, Iqra Farooq +3
Cardiovascular disease (CVD) risk stratification remains a major challenge due to its multifactorial nature and limited availability of high-quality labeled datasets. While genomic…
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…
Focal Modulation and Bidirectional Feature Fusion Network for Medical Image Segmentation
Moin Safdar, Shahzaib Iqbal, Mubeen Ghafoor +4
Medical image segmentation is essential for clinical applications such as disease diagnosis, treatment planning, and disease development monitoring because it provides precise morp…
RELOOP: Recursive Retrieval with Multi-Hop Reasoner and Planners for Heterogeneous QA
Ruiyi Yang, Hao Xue, Imran Razzak +2
Retrieval-augmented generation (RAG) remains brittle on multi-step questions and heterogeneous evidence sources, trading accuracy against latency and token/tool budgets. This paper…
SAM-DCE: Decoupled Context Enhancement for Prompt-Free Medical Image Segmentation
Yingzhen Hu, Yiheng Zhong, Ruobing Li +8
The Segment Anything Model (SAM) is a promising foundation model for medical image segmentation, but its prompt-driven design is not directly suitable for fully automatic multi-cla…
Towards Robust Visual Continual Learning with Multi-Prototype Supervision
Xiwei Liu, Yulong Li, Yichen Li +4
Language-guided supervision, which utilizes a frozen semantic target from a Pretrained Language Model (PLM), has emerged as a promising paradigm for visual Continual Learning (CL).…
A Knowledge-driven Adaptive Collaboration of LLMs for Enhancing Medical Decision-making
Xiao Wu, Ting-Zhu Huang, Liang-Jian Deng +3
Medical decision-making often involves integrating knowledge from multiple clinical specialties, typically achieved through multidisciplinary teams. Inspired by this collaborative…
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…
Task Allocation for Autonomous Machines using Computational Intelligence and Deep Reinforcement Learning
Thanh Thi Nguyen, Quoc Viet Hung Nguyen, Jonathan Kua +3
Enabling multiple autonomous machines to perform reliably requires the development of efficient cooperative control algorithms. This paper presents a survey of algorithms that have…
A Machine Learning Approach to Predict Biological Age and its Longitudinal Drivers
Nazira Dunbayeva, Yulong Li, Yutong Xie +1
Predicting an individual's aging trajectory is a central challenge in preventative medicine and bioinformatics. While machine learning models can predict chronological age from bio…
How Effectively Can Large Language Models Connect SNP Variants and ECG Phenotypes for Cardiovascular Risk Prediction?
Niranjana Arun Menon, Iqra Farooq, Yulong Li +4
Cardiovascular disease (CVD) prediction remains a tremendous challenge due to its multifactorial etiology and global burden of morbidity and mortality. Despite the growing availabi…
scAGC: Learning Adaptive Cell Graphs with Contrastive Guidance for Single-Cell Clustering
Huifa Li, Jie Fu, Xinlin Zhuang +6
Accurate cell type annotation is a crucial step in analyzing single-cell RNA sequencing (scRNA-seq) data, which provides valuable insights into cellular heterogeneity. However, due…
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…
A Survey of Scientific Large Language Models: From Data Foundations to Agent Frontiers
Ming Hu, Chenglong Ma, Wei Li +117
Scientific Large Language Models (Sci-LLMs) are transforming how knowledge is represented, integrated, and applied in scientific research, yet their progress is shaped by the compl…