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adapters 1large language models 1mixture of experts 1multi-task learning 1parameter-efficient fine-tuning 1

From the 1 of 1 linked paper with an AI index.

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1 paper

cs.CL2024

MoDE: Effective Multi-task Parameter Efficient Fine-Tuning with a Mixture of Dyadic Experts

Lin Ning, Harsh Lara, Meiqi Guo +1

The paper introduces MoDE, a multi-task parameter-efficient fine-tuning method for large language models that shares down-projection matrices and uses rank-one adapters with task r…