Develops a constrained bandit algorithm for online LLM selection under packing and covering constraints with time-varying demand, claiming sublinear regret and constraint violations versus an offline full-information benchmark.
Local-cloud inference offloading for llms in multi-modal, multi-task, multi- dialogue settings,
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Online LLM Selection via Constrained Bandits with Time-Varying Demand
Develops a constrained bandit algorithm for online LLM selection under packing and covering constraints with time-varying demand, claiming sublinear regret and constraint violations versus an offline full-information benchmark.