collaborators

5 papers

cs.AI2026

CoRCi: Cross-Reconstruction of Coherent Interests Modeling in Cross-Domain Sequential Recommendation

Qingtian Bian, Tieying Li, Marcus de Carvalho +3

Cross-Domain Sequential Recommendation (CDSR) aims to alleviate data sparsity by transferring dynamic user interests across related domains. A key challenge lies in effectively bri…

cs.IR2026

Context-Aware Disentanglement for Cross-Domain Sequential Recommendation: A Causal View

Xingzi Wang, Qingtian Bian, Hui Fang

Cross-Domain Sequential Recommendation (CDSR) aims to en-hance recommendation quality by transferring knowledge across domains, offering effective solutions to data sparsity and co…

eess.IV2025

Multi-Atlas Brain Network Classification through Consistency Distillation and Complementary Information Fusion

Jiaxing Xu, Mengcheng Lan, Xia Dong +4

In the realm of neuroscience, identifying distinctive patterns associated with neurological disorders via brain networks is crucial. Resting-state functional magnetic resonance ima…

cs.IR2025

ABXI: Invariant Interest Adaptation for Task-Guided Cross-Domain Sequential Recommendation

Qingtian Bian, Marcus Vinícius de Carvalho, Tieying Li +3

Cross-Domain Sequential Recommendation (CDSR) has recently gained attention for countering data sparsity by transferring knowledge across domains. A common approach merges domain-s…

cs.LG2025

BrainOOD: Out-of-distribution Generalizable Brain Network Analysis

Jiaxing Xu, Yongqiang Chen, Xia Dong +5

In neuroscience, identifying distinct patterns linked to neurological disorders, such as Alzheimer's and Autism, is critical for early diagnosis and effective intervention. Graph N…