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20232026
most citedConvergence Analysis of Split Federated Learning on Heterogeneous Data

1 citations · 2 across the 6 of their papers we have counts for

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cs.LG2026

ZeroLock: Concurrent Memory-Efficient LLM Training via Modular Update Decoupling

Wentao Dai, Xuanran Li, Yuxiang Zhang +2

Large language model (LLM) fine-tuning at the edge adapts the model to scenario-specific data while preserving privacy. Although existing studies proposed pipeline parallelism to a…

cs.LG2026

Decoupled Split Learning via Auxiliary Loss

Anower Zihad, Felix Owino, Ming Tang +1

Split learning is a distributed training paradigm where a neural network is partitioned between clients and a server, which allows data to remain at the client while only intermedi…