LoRA-Adv: Boosting Text Classification in Large Language Models Through Adversarial Low-Rank Adaptations
Low-rank adaptation (LoRA), a paradigm bridging the gap between large language models and fine-tuning, has demonstrated effectiveness across various natural language processing tasks. The LoRA algorithm updates only a small number of model parameters, significantly reducing the consumption of comput...
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| 主要な著者: | , , , , |
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| フォーマット: | Artigo |
| 言語: | Inglês |
| 出版事項: |
IEEE
2025-01-01
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| シリーズ: | IEEE Access |
| 主題: | |
| オンライン･アクセス: | https://ieeexplore.ieee.org/document/11036123/ |
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