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As of Oct 16, on arXiv:2610.20753, the authors say client resource limits make a shared server-client architecture impractical for federated learning of large language models.
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Paper proposes Optimal Hydra, data-informed Hydra-Nets for federated LLM training across heterogeneous client models
Posted on arXiv on Oct 16, 2026 (source: arxiv.org).
On arXiv:2610.20753, the authors say client resource limits make a shared server-client architecture impractical for federated learning of large language models. Optimal Hydra uses data-informed Hydra-Nets to support model-heterogeneous federated learning for LLMs. The paper has not yet been peer-reviewed.
Source: arXiv cs.LG
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