67 citations · 108 across the 7 of their papers we have counts for
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cs.CL2020
AdapterHub: A Framework for Adapting Transformers
Jonas Pfeiffer, Andreas Rücklé, Clifton Poth +5
The current modus operandi in NLP involves downloading and fine-tuning pre-trained models consisting of millions or billions of parameters. Storing and sharing such large trained m…
cs.CL2020
AdapterFusion: Non-Destructive Task Composition for Transfer Learning
Jonas Pfeiffer, Aishwarya Kamath, Andreas Rücklé +2
Sequential fine-tuning and multi-task learning are methods aiming to incorporate knowledge from multiple tasks; however, they suffer from catastrophic forgetting and difficulties i…