Author

Rawad Bitar

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#artificial intelligence Preprint Aug 2026

RW-LoRA: Communication-Efficient Decentralized LoRA Fine-Tuning via Random Walks

A random-walk-based LoRA fine-tuning scheme that eliminates the need for global synchronization, substantially reduces communication and computation costs, and avoids aggregation errors is proposed and provides rigorous convergence guarantees for non-convex objectives under standard assumptions.

Xing-Ran Chen, Rohit Bhagat, Ghadir Ayache et al. · 0 citations

Preprint Aug 2026

SeFoRA: Sketch-Aggregated Federated Low-Rank Adaptation with Heterogeneous Client Ranks

This work proposes SeFoRA, a sketch-aggregated federated LoRA algorithm in which each client transmits a linear sketch of its local updates, enabling direct aggregation at the federator, and introduces a rank-homogeneous version called SeFoRA-Ho which allows for direct adapter aggregation in this setting.

Yue Xia, Tayyebeh Jahani-Nezhad, Mayank Bakshi et al. · 2 citations