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Review Open access Sep 2026

Federated Fine-Tuning of Large Language Models on Resource-Constrained Clients: Technical Approaches, Resource Costs, and Applicability

This review examines four composable routes---parameter-efficient and quantized adaptation, backpropagation-free adaptation, proxy or submodel adaptation, and split federated adaptation---through a common framework that traces the objects each endpoint retains, exchanges, and discloses.

Yun-Heng Shen, Xiao Liu, Yang Yang et al. · 1 citation
#artificial intelligence Preprint Sep 2026

Explainable Recommendations at Scale: LLM Rationales for YouTube Music Artist Discovery

This paper presents an industry case study of a decoupled recommendation architecture that successfully scales exploration without compromising latency, and demonstrates that combining LLM-backed recommendations with these explanatory rationales significantly reduces the trust barrier for new content.

Xiao Liu, Yan-Wei Song, Srivaths Ranganathan et al. · 0 citations

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