research19h
ARIADNE: Agnostic Routing for Inference-time Adapter DyNamic sElection
Researchers propose ARIADNE, a method for dynamically selecting adapters for PEFT models at inference time without needing access to adapter internals. The approach uses only input embeddings and adapter outputs to make routing decisions. This allows for more flexible and scalable deployment of PEFT models in real-world applications. You can apply this method to improve adapter selection in your own PEFT workflows.
Key takeaways
- ARIADNE uses only input embeddings and adapter outputs for routing.
- No need for adapter internals like weights or gradients.
- Enables scalable PEFT deployment with heterogeneous adapter pools.