FedHLM uses federated learning to learn token-level uncertainty thresholds that decide when to offload tokens from a small edge LM to a large cloud LM, claiming a 95 percent reduction in LLM transmissions.
QoSBERT: An Uncertainty- Aware Approach based on Pre-trained Language Models for Service Quality Prediction,
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Federated Learning-Enabled Hybrid Language Models for Communication-Efficient Token Transmission
FedHLM uses federated learning to learn token-level uncertainty thresholds that decide when to offload tokens from a small edge LM to a large cloud LM, claiming a 95 percent reduction in LLM transmissions.