Papers by Rushi Qiang
AutoLoRA: Automatically Tuning Matrix Ranks in Low-Rank Adaptation Based on Meta Learning (2024.naacl-long)
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| Challenge: | Large-scale pretraining followed by task-specific finetuning has achieved great success in various NLP tasks. |
| Approach: | They propose a meta learning based framework for automatically identifying the optimal rank of each LoRA layer. |
| Outcome: | The proposed framework is based on a meta learning based framework that can identify the optimal rank of each LoRA layer. |