Author

Qing Tian

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#machine learning Preprint Sep 2026

CALM: Class-wise Agreement and Label-gated Disagreement Modulation for Decentralized Federated Learning

CALM is proposed, which replaces every hard decision with a smooth trust gate at three levels: per class, teachers are weighted by agreement with the peer consensus; per sample, distillation is scaled by the teachers'divergence from that target; and a label gate scales it by how strongly the target supports the sample'...

Yilong Ying, Qing Tian · 0 citations

#machine learning Preprint Aug 2026

CRAD: Class-wise Reliability-Aware Distillation for Decentralized Heterogeneous Federated Learning

This work proposes Class-wise Reliability-Aware Distillation (CRAD), which, per class, first discards teachers that disagree with the peer consensus and then takes a weighted average of the rest, weighting each teacher by its per-class reliability (precision, or inverse variance).

Baraa Bilbeisi, Meng-Chen Fan, Bao-Cheng Geng et al. · 1 citation