3260 papers • 126 benchmarks • 313 datasets
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These leaderboards are used to track progress in device-cloud-collaboration-23
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Use these libraries to find device-cloud-collaboration-23 models and implementations
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It is argued that the computational cost brought by fine-tuning can be rather unnecessary, and a novel perspective to improving DMG without increasing computational cost is presented, i.e., device-specific parameter generation which directly maps data distribution to parameters.
Adding a benchmark result helps the community track progress.