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cs.LG2024
Hyperband-based Bayesian Optimization for Black-box Prompt Selection
Lennart Schneider, Martin Wistuba, Aaron Klein +3
Optimal prompt selection is crucial for maximizing large language model (LLM) performance on downstream tasks, especially in black-box settings where models are only accessible via…
cs.LG2024
Choice of PEFT Technique in Continual Learning: Prompt Tuning is Not All You Need
Martin Wistuba, Prabhu Teja Sivaprasad, Lukas Balles +1
Recent Continual Learning (CL) methods have combined pretrained Transformers with prompt tuning, a parameter-efficient fine-tuning (PEFT) technique. We argue that the choice of pro…