
The author proposes the Mixture-of-LoRAs (MoA) architecture as an efficient tuning method for multitask learning with large language models, addressing interference between tasks and enhancing performance.


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mixture-of-loras-efficient-multitask-tuning-for-large-language-models


Mixture-of-LoRAs: Efficient Multitask Tuning for Large Language Models


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提案されたMixture-of-LoRAs（MoA）アーキテクチャは、大規模言語モデルに対する効率的なマルチタスクファインチューニング手法を提供し、タスク間の干渉とトレーニングの不安定性に対処します。


mixture-of-loras-an-efficient-multitask-tuning-for-large-language-models


Mixture-of-LoRAs: An Efficient Multitask Tuning for Large Language Models



Mixture-of-LoRAs (MoA) architecture enhances multitask learning for Large Language Models (LLMs) by preventing interference between tasks and improving performance.
