arXiv Machine Learning June 30, 2026 By Guiquan Sun, Xikun Zhang, Jingchao Ni, Dongjin Song

DRIFT: A Benchmark for Task-Free Continual Graph Learning with Continuous Distribution Shifts

Read the original on arXiv Machine Learning →

arXiv:2605. 12998v3 Announce Type: replace Abstract: Continual graph learning (CGL) aims to learn from dynamically evolving graphs while mitigating catastrophic forgetting.

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

benchmarks

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computer-vision reinforcement-learning benchmarks safety

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Theoretical Foundations of Continual Learning via Drift-Plus-Penalty

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benchmarks

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llms fine-tuning multimodal benchmarks

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agents multimodal benchmarks

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