Abstract: Highlights•Addressed key issues: limited mini-batch samples and false positives in GCD.•Proposed a robust Divide-and-Combine strategy for efficient representation learning.•Analyzed the cluster-level alignment and uniformity of contrastive loss in GCD.•Unified system for efficient representation learning and reliable category discovery.
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