arXiv Machine Learning June 2, 2026 By Yuhan Wang, Yibo Ding, Yutong Ye, Mufan Zhao, Wenbo Zhang, Ruijie Wang, Jianxin Li

G2LoRA: Gradient Orthogonal Low-Rank Adaptation Framework for Graph Continual Learning on Text-Attributed Graphs

Read the original on arXiv Machine Learning →

arXiv:2606. 01873v1 Announce Type: new Abstract: LLM-as-Aligner has emerged as a prevalent pre-training paradigm for Text-Attributed Graphs(TAGS), aligning graph and text modalities into a shared embedding space via CLIP-style contrastive learning.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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UNIT: Unleash Large Language Models Potential for Graph Continual Learning

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CP-MoE: Consistency-Preserving Mixture-of-Experts for Continual Learning

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