arXiv Machine Learning September 1, 2026 By Hojin Kim, Sujin Yoon, Sungsu Lim, Dongwon Lee, David Yoon Suk Kang

Who Should Teach? Confidence-Aware Dual-Teacher Learning for Few-Shot Node Classification on Text-Attributed Graphs

Read the original on arXiv Machine Learning →

The paper introduces CoTeach, a confidence‑aware dual‑teacher learning framework for few‑shot node classification on text‑attributed graphs. It dynamically chooses between a Graph Neural Network and a Large Language Model as the teacher for each node, based on which source is more reliable for that node. Experiments show that this approach improves classification accuracy while cutting unnecessary use of expensive LLMs.

Machine-generated by The Flow from the publisher's headline and feed description — not written or checked by a human. The full article lives at arXiv Machine Learning.

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