catastrophic forgetting 1continual learning 1federated learning 1graph neural networks 1memory preservation 1multimodal learning 1
From the 1 of 16 linked papers with an AI index.
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cs.AI2026
OpenRTAG: A Comprehensive Benchmark for Robust Text-Attributed Graph Learning under Data Quality Degradation
Yuze Dai, Zhihan Zhang, Yan Zhao +6
Text-attributed graphs (TAGs) are an important graph data form that combine relational structure with rich node text. However, real-world TAGs are often imperfect, with quality iss…
cs.AI2026
The Patient is not a Moving Document: A World Model Training Paradigm for Longitudinal EHR
Irsyad Adam, Zekai Chen, David Laprade +5
Large language models (LLMs) trained with next-word-prediction have achieved success as clinical foundation models. Representations from these language backbones yield strong linea…
cs.AI2026
LION: A Clifford Neural Paradigm for Multimodal-Attributed Graph Learning
Xunkai Li, Zhengyu Wu, Zekai Chen +6
Recently, the rapid advancement of multimodal domains has driven a data-centric paradigm shift in graph ML, transitioning from text-attributed to multimodal-attributed graphs. This…