Papers with curriculum-guided,

    1 papers
    GenDis: Generative-Discriminative Dual-View Co-Training for Generalized Category Discovery (2026.acl-long)

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    Challenge: Existing methods rely on one-hot discriminative supervision, leading to overfitting on seen classes and poor generalization to unseen ones.
    Approach: They propose a Generative–Discriminative Dual-View Co-Training framework that unifies discriminative classification and semantic label generation within an LLM.
    Outcome: The proposed framework outperforms existing methods on five benchmarks on the generalized category discovery (GCD) task.

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