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Forgotten prompts can be extracted from unlearned models with 100% accuracy using just a fraction of the queries required by traditional methods.
FoMoE shatters the full-replica barrier, enabling efficient LLM training across weakly connected data centers with unprecedented communication and memory savings.
PreLort ensures that low-rank clients can leverage the richer information from higher-rank clients, leading to significant improvements in model performance.
Achieve LLM-level performance with significantly reduced latency and enhanced privacy by offloading specialized tasks to edge devices using a federated LLM-SLM architecture.
