LNTrust has nodes learn compact trust functions from validation evidence that both guide training distillation and define deployment ensembles, yielding higher accuracy with less communication than prior output-only baselines.
Model-contrastive federated learning
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ForgeVLA enables federated VLA model training from unlabeled vision-action pairs by recovering language via embodied classifiers and using contrastive planning plus adaptive aggregation to avoid feature collapse.
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Learned Neighbor Trust for Collaborative Deployment in Model-Agnostic Decentralized Learning
LNTrust has nodes learn compact trust functions from validation evidence that both guide training distillation and define deployment ensembles, yielding higher accuracy with less communication than prior output-only baselines.